first commit
This commit is contained in:
xxl
parent
8973032771
commit
7333ed114f
537
README.md
537
README.md
|
|
@ -1,3 +1,536 @@
|
|||
# gemma-3-4b-it
|
||||
---
|
||||
license: gemma
|
||||
library_name: transformers
|
||||
pipeline_tag: image-text-to-text
|
||||
extra_gated_heading: Access Gemma on Hugging Face
|
||||
extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and
|
||||
agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging
|
||||
Face and click below. Requests are processed immediately.
|
||||
extra_gated_button_content: Acknowledge license
|
||||
base_model: google/gemma-3-4b-pt
|
||||
---
|
||||
|
||||
gemma-3-4b-it
|
||||
# Gemma 3 model card
|
||||
|
||||
**Model Page**: [Gemma](https://ai.google.dev/gemma/docs/core)
|
||||
|
||||
**Resources and Technical Documentation**:
|
||||
|
||||
* [Gemma 3 Technical Report][g3-tech-report]
|
||||
* [Responsible Generative AI Toolkit][rai-toolkit]
|
||||
* [Gemma on Kaggle][kaggle-gemma]
|
||||
* [Gemma on Vertex Model Garden][vertex-mg-gemma3]
|
||||
|
||||
**Terms of Use**: [Terms][terms]
|
||||
|
||||
**Authors**: Google DeepMind
|
||||
|
||||
## Model Information
|
||||
|
||||
Summary description and brief definition of inputs and outputs.
|
||||
|
||||
### Description
|
||||
|
||||
Gemma is a family of lightweight, state-of-the-art open models from Google,
|
||||
built from the same research and technology used to create the Gemini models.
|
||||
Gemma 3 models are multimodal, handling text and image input and generating text
|
||||
output, with open weights for both pre-trained variants and instruction-tuned
|
||||
variants. Gemma 3 has a large, 128K context window, multilingual support in over
|
||||
140 languages, and is available in more sizes than previous versions. Gemma 3
|
||||
models are well-suited for a variety of text generation and image understanding
|
||||
tasks, including question answering, summarization, and reasoning. Their
|
||||
relatively small size makes it possible to deploy them in environments with
|
||||
limited resources such as laptops, desktops or your own cloud infrastructure,
|
||||
democratizing access to state of the art AI models and helping foster innovation
|
||||
for everyone.
|
||||
|
||||
### Inputs and outputs
|
||||
|
||||
- **Input:**
|
||||
- Text string, such as a question, a prompt, or a document to be summarized
|
||||
- Images, normalized to 896 x 896 resolution and encoded to 256 tokens
|
||||
each
|
||||
- Total input context of 128K tokens for the 4B, 12B, and 27B sizes, and
|
||||
32K tokens for the 1B size
|
||||
|
||||
- **Output:**
|
||||
- Generated text in response to the input, such as an answer to a
|
||||
question, analysis of image content, or a summary of a document
|
||||
- Total output context of 8192 tokens
|
||||
|
||||
### Usage
|
||||
|
||||
Below, there are some code snippets on how to get quickly started with running the model. First, install the Transformers library with the version made for Gemma 3:
|
||||
|
||||
```sh
|
||||
$ pip install git+https://github.com/huggingface/transformers@v4.49.0-Gemma-3
|
||||
```
|
||||
|
||||
Then, copy the snippet from the section that is relevant for your use case.
|
||||
|
||||
#### Running with the `pipeline` API
|
||||
|
||||
You can initialize the model and processor for inference with `pipeline` as follows.
|
||||
|
||||
```python
|
||||
from transformers import pipeline
|
||||
import torch
|
||||
|
||||
pipe = pipeline(
|
||||
"image-text-to-text",
|
||||
model="google/gemma-3-4b-it",
|
||||
device="cuda",
|
||||
torch_dtype=torch.bfloat16
|
||||
)
|
||||
```
|
||||
|
||||
With instruction-tuned models, you need to use chat templates to process our inputs first. Then, you can pass it to the pipeline.
|
||||
|
||||
```python
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": [{"type": "text", "text": "You are a helpful assistant."}]
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
|
||||
{"type": "text", "text": "What animal is on the candy?"}
|
||||
]
|
||||
}
|
||||
]
|
||||
|
||||
output = pipe(text=messages, max_new_tokens=200)
|
||||
print(output[0][0]["generated_text"][-1]["content"])
|
||||
# Okay, let's take a look!
|
||||
# Based on the image, the animal on the candy is a **turtle**.
|
||||
# You can see the shell shape and the head and legs.
|
||||
```
|
||||
|
||||
#### Running the model on a single/multi GPU
|
||||
|
||||
```python
|
||||
# pip install accelerate
|
||||
|
||||
from transformers import AutoProcessor, Gemma3ForConditionalGeneration
|
||||
from PIL import Image
|
||||
import requests
|
||||
import torch
|
||||
|
||||
model_id = "google/gemma-3-4b-it"
|
||||
|
||||
model = Gemma3ForConditionalGeneration.from_pretrained(
|
||||
model_id, device_map="auto"
|
||||
).eval()
|
||||
|
||||
processor = AutoProcessor.from_pretrained(model_id)
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": [{"type": "text", "text": "You are a helpful assistant."}]
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "image", "image": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/bee.jpg"},
|
||||
{"type": "text", "text": "Describe this image in detail."}
|
||||
]
|
||||
}
|
||||
]
|
||||
|
||||
inputs = processor.apply_chat_template(
|
||||
messages, add_generation_prompt=True, tokenize=True,
|
||||
return_dict=True, return_tensors="pt"
|
||||
).to(model.device, dtype=torch.bfloat16)
|
||||
|
||||
input_len = inputs["input_ids"].shape[-1]
|
||||
|
||||
with torch.inference_mode():
|
||||
generation = model.generate(**inputs, max_new_tokens=100, do_sample=False)
|
||||
generation = generation[0][input_len:]
|
||||
|
||||
decoded = processor.decode(generation, skip_special_tokens=True)
|
||||
print(decoded)
|
||||
|
||||
# **Overall Impression:** The image is a close-up shot of a vibrant garden scene,
|
||||
# focusing on a cluster of pink cosmos flowers and a busy bumblebee.
|
||||
# It has a slightly soft, natural feel, likely captured in daylight.
|
||||
```
|
||||
|
||||
|
||||
### Citation
|
||||
|
||||
```none
|
||||
@article{gemma_2025,
|
||||
title={Gemma 3},
|
||||
url={https://goo.gle/Gemma3Report},
|
||||
publisher={Kaggle},
|
||||
author={Gemma Team},
|
||||
year={2025}
|
||||
}
|
||||
```
|
||||
|
||||
## Model Data
|
||||
|
||||
Data used for model training and how the data was processed.
|
||||
|
||||
### Training Dataset
|
||||
|
||||
These models were trained on a dataset of text data that includes a wide variety
|
||||
of sources. The 27B model was trained with 14 trillion tokens, the 12B model was
|
||||
trained with 12 trillion tokens, 4B model was trained with 4 trillion tokens and
|
||||
1B with 2 trillion tokens. Here are the key components:
|
||||
|
||||
- Web Documents: A diverse collection of web text ensures the model is
|
||||
exposed to a broad range of linguistic styles, topics, and vocabulary. The
|
||||
training dataset includes content in over 140 languages.
|
||||
- Code: Exposing the model to code helps it to learn the syntax and
|
||||
patterns of programming languages, which improves its ability to generate
|
||||
code and understand code-related questions.
|
||||
- Mathematics: Training on mathematical text helps the model learn logical
|
||||
reasoning, symbolic representation, and to address mathematical queries.
|
||||
- Images: A wide range of images enables the model to perform image
|
||||
analysis and visual data extraction tasks.
|
||||
|
||||
The combination of these diverse data sources is crucial for training a powerful
|
||||
multimodal model that can handle a wide variety of different tasks and data
|
||||
formats.
|
||||
|
||||
### Data Preprocessing
|
||||
|
||||
Here are the key data cleaning and filtering methods applied to the training
|
||||
data:
|
||||
|
||||
- CSAM Filtering: Rigorous CSAM (Child Sexual Abuse Material) filtering
|
||||
was applied at multiple stages in the data preparation process to ensure
|
||||
the exclusion of harmful and illegal content.
|
||||
- Sensitive Data Filtering: As part of making Gemma pre-trained models
|
||||
safe and reliable, automated techniques were used to filter out certain
|
||||
personal information and other sensitive data from training sets.
|
||||
- Additional methods: Filtering based on content quality and safety in
|
||||
line with [our policies][safety-policies].
|
||||
|
||||
## Implementation Information
|
||||
|
||||
Details about the model internals.
|
||||
|
||||
### Hardware
|
||||
|
||||
Gemma was trained using [Tensor Processing Unit (TPU)][tpu] hardware (TPUv4p,
|
||||
TPUv5p and TPUv5e). Training vision-language models (VLMS) requires significant
|
||||
computational power. TPUs, designed specifically for matrix operations common in
|
||||
machine learning, offer several advantages in this domain:
|
||||
|
||||
- Performance: TPUs are specifically designed to handle the massive
|
||||
computations involved in training VLMs. They can speed up training
|
||||
considerably compared to CPUs.
|
||||
- Memory: TPUs often come with large amounts of high-bandwidth memory,
|
||||
allowing for the handling of large models and batch sizes during training.
|
||||
This can lead to better model quality.
|
||||
- Scalability: TPU Pods (large clusters of TPUs) provide a scalable
|
||||
solution for handling the growing complexity of large foundation models.
|
||||
You can distribute training across multiple TPU devices for faster and more
|
||||
efficient processing.
|
||||
- Cost-effectiveness: In many scenarios, TPUs can provide a more
|
||||
cost-effective solution for training large models compared to CPU-based
|
||||
infrastructure, especially when considering the time and resources saved
|
||||
due to faster training.
|
||||
- These advantages are aligned with
|
||||
[Google's commitments to operate sustainably][sustainability].
|
||||
|
||||
### Software
|
||||
|
||||
Training was done using [JAX][jax] and [ML Pathways][ml-pathways].
|
||||
|
||||
JAX allows researchers to take advantage of the latest generation of hardware,
|
||||
including TPUs, for faster and more efficient training of large models. ML
|
||||
Pathways is Google's latest effort to build artificially intelligent systems
|
||||
capable of generalizing across multiple tasks. This is specially suitable for
|
||||
foundation models, including large language models like these ones.
|
||||
|
||||
Together, JAX and ML Pathways are used as described in the
|
||||
[paper about the Gemini family of models][gemini-2-paper]; *"the 'single
|
||||
controller' programming model of Jax and Pathways allows a single Python
|
||||
process to orchestrate the entire training run, dramatically simplifying the
|
||||
development workflow."*
|
||||
|
||||
## Evaluation
|
||||
|
||||
Model evaluation metrics and results.
|
||||
|
||||
### Benchmark Results
|
||||
|
||||
These models were evaluated against a large collection of different datasets and
|
||||
metrics to cover different aspects of text generation:
|
||||
|
||||
#### Reasoning and factuality
|
||||
|
||||
| Benchmark | Metric | Gemma 3 PT 1B | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |
|
||||
| ------------------------------ |----------------|:--------------:|:-------------:|:--------------:|:--------------:|
|
||||
| [HellaSwag][hellaswag] | 10-shot | 62.3 | 77.2 | 84.2 | 85.6 |
|
||||
| [BoolQ][boolq] | 0-shot | 63.2 | 72.3 | 78.8 | 82.4 |
|
||||
| [PIQA][piqa] | 0-shot | 73.8 | 79.6 | 81.8 | 83.3 |
|
||||
| [SocialIQA][socialiqa] | 0-shot | 48.9 | 51.9 | 53.4 | 54.9 |
|
||||
| [TriviaQA][triviaqa] | 5-shot | 39.8 | 65.8 | 78.2 | 85.5 |
|
||||
| [Natural Questions][naturalq] | 5-shot | 9.48 | 20.0 | 31.4 | 36.1 |
|
||||
| [ARC-c][arc] | 25-shot | 38.4 | 56.2 | 68.9 | 70.6 |
|
||||
| [ARC-e][arc] | 0-shot | 73.0 | 82.4 | 88.3 | 89.0 |
|
||||
| [WinoGrande][winogrande] | 5-shot | 58.2 | 64.7 | 74.3 | 78.8 |
|
||||
| [BIG-Bench Hard][bbh] | few-shot | 28.4 | 50.9 | 72.6 | 77.7 |
|
||||
| [DROP][drop] | 1-shot | 42.4 | 60.1 | 72.2 | 77.2 |
|
||||
|
||||
[hellaswag]: https://arxiv.org/abs/1905.07830
|
||||
[boolq]: https://arxiv.org/abs/1905.10044
|
||||
[piqa]: https://arxiv.org/abs/1911.11641
|
||||
[socialiqa]: https://arxiv.org/abs/1904.09728
|
||||
[triviaqa]: https://arxiv.org/abs/1705.03551
|
||||
[naturalq]: https://github.com/google-research-datasets/natural-questions
|
||||
[arc]: https://arxiv.org/abs/1911.01547
|
||||
[winogrande]: https://arxiv.org/abs/1907.10641
|
||||
[bbh]: https://paperswithcode.com/dataset/bbh
|
||||
[drop]: https://arxiv.org/abs/1903.00161
|
||||
|
||||
#### STEM and code
|
||||
|
||||
| Benchmark | Metric | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |
|
||||
| ------------------------------ |----------------|:-------------:|:--------------:|:--------------:|
|
||||
| [MMLU][mmlu] | 5-shot | 59.6 | 74.5 | 78.6 |
|
||||
| [MMLU][mmlu] (Pro COT) | 5-shot | 29.2 | 45.3 | 52.2 |
|
||||
| [AGIEval][agieval] | 3-5-shot | 42.1 | 57.4 | 66.2 |
|
||||
| [MATH][math] | 4-shot | 24.2 | 43.3 | 50.0 |
|
||||
| [GSM8K][gsm8k] | 8-shot | 38.4 | 71.0 | 82.6 |
|
||||
| [GPQA][gpqa] | 5-shot | 15.0 | 25.4 | 24.3 |
|
||||
| [MBPP][mbpp] | 3-shot | 46.0 | 60.4 | 65.6 |
|
||||
| [HumanEval][humaneval] | 0-shot | 36.0 | 45.7 | 48.8 |
|
||||
|
||||
[mmlu]: https://arxiv.org/abs/2009.03300
|
||||
[agieval]: https://arxiv.org/abs/2304.06364
|
||||
[math]: https://arxiv.org/abs/2103.03874
|
||||
[gsm8k]: https://arxiv.org/abs/2110.14168
|
||||
[gpqa]: https://arxiv.org/abs/2311.12022
|
||||
[mbpp]: https://arxiv.org/abs/2108.07732
|
||||
[humaneval]: https://arxiv.org/abs/2107.03374
|
||||
|
||||
#### Multilingual
|
||||
|
||||
| Benchmark | Gemma 3 PT 1B | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |
|
||||
| ------------------------------------ |:-------------:|:-------------:|:--------------:|:--------------:|
|
||||
| [MGSM][mgsm] | 2.04 | 34.7 | 64.3 | 74.3 |
|
||||
| [Global-MMLU-Lite][global-mmlu-lite] | 24.9 | 57.0 | 69.4 | 75.7 |
|
||||
| [WMT24++][wmt24pp] (ChrF) | 36.7 | 48.4 | 53.9 | 55.7 |
|
||||
| [FloRes][flores] | 29.5 | 39.2 | 46.0 | 48.8 |
|
||||
| [XQuAD][xquad] (all) | 43.9 | 68.0 | 74.5 | 76.8 |
|
||||
| [ECLeKTic][eclektic] | 4.69 | 11.0 | 17.2 | 24.4 |
|
||||
| [IndicGenBench][indicgenbench] | 41.4 | 57.2 | 61.7 | 63.4 |
|
||||
|
||||
[mgsm]: https://arxiv.org/abs/2210.03057
|
||||
[flores]: https://arxiv.org/abs/2106.03193
|
||||
[xquad]: https://arxiv.org/abs/1910.11856v3
|
||||
[global-mmlu-lite]: https://huggingface.co/datasets/CohereForAI/Global-MMLU-Lite
|
||||
[wmt24pp]: https://arxiv.org/abs/2502.12404v1
|
||||
[eclektic]: https://arxiv.org/abs/2502.21228
|
||||
[indicgenbench]: https://arxiv.org/abs/2404.16816
|
||||
|
||||
#### Multimodal
|
||||
|
||||
| Benchmark | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |
|
||||
| ------------------------------ |:-------------:|:--------------:|:--------------:|
|
||||
| [COCOcap][coco-cap] | 102 | 111 | 116 |
|
||||
| [DocVQA][docvqa] (val) | 72.8 | 82.3 | 85.6 |
|
||||
| [InfoVQA][info-vqa] (val) | 44.1 | 54.8 | 59.4 |
|
||||
| [MMMU][mmmu] (pt) | 39.2 | 50.3 | 56.1 |
|
||||
| [TextVQA][textvqa] (val) | 58.9 | 66.5 | 68.6 |
|
||||
| [RealWorldQA][realworldqa] | 45.5 | 52.2 | 53.9 |
|
||||
| [ReMI][remi] | 27.3 | 38.5 | 44.8 |
|
||||
| [AI2D][ai2d] | 63.2 | 75.2 | 79.0 |
|
||||
| [ChartQA][chartqa] | 63.6 | 74.7 | 76.3 |
|
||||
| [VQAv2][vqav2] | 63.9 | 71.2 | 72.9 |
|
||||
| [BLINK][blinkvqa] | 38.0 | 35.9 | 39.6 |
|
||||
| [OKVQA][okvqa] | 51.0 | 58.7 | 60.2 |
|
||||
| [TallyQA][tallyqa] | 42.5 | 51.8 | 54.3 |
|
||||
| [SpatialSense VQA][ss-vqa] | 50.9 | 60.0 | 59.4 |
|
||||
| [CountBenchQA][countbenchqa] | 26.1 | 17.8 | 68.0 |
|
||||
|
||||
[coco-cap]: https://cocodataset.org/#home
|
||||
[docvqa]: https://www.docvqa.org/
|
||||
[info-vqa]: https://arxiv.org/abs/2104.12756
|
||||
[mmmu]: https://arxiv.org/abs/2311.16502
|
||||
[textvqa]: https://textvqa.org/
|
||||
[realworldqa]: https://paperswithcode.com/dataset/realworldqa
|
||||
[remi]: https://arxiv.org/html/2406.09175v1
|
||||
[ai2d]: https://allenai.org/data/diagrams
|
||||
[chartqa]: https://arxiv.org/abs/2203.10244
|
||||
[vqav2]: https://visualqa.org/index.html
|
||||
[blinkvqa]: https://arxiv.org/abs/2404.12390
|
||||
[okvqa]: https://okvqa.allenai.org/
|
||||
[tallyqa]: https://arxiv.org/abs/1810.12440
|
||||
[ss-vqa]: https://arxiv.org/abs/1908.02660
|
||||
[countbenchqa]: https://github.com/google-research/big_vision/blob/main/big_vision/datasets/countbenchqa/
|
||||
|
||||
## Ethics and Safety
|
||||
|
||||
Ethics and safety evaluation approach and results.
|
||||
|
||||
### Evaluation Approach
|
||||
|
||||
Our evaluation methods include structured evaluations and internal red-teaming
|
||||
testing of relevant content policies. Red-teaming was conducted by a number of
|
||||
different teams, each with different goals and human evaluation metrics. These
|
||||
models were evaluated against a number of different categories relevant to
|
||||
ethics and safety, including:
|
||||
|
||||
- **Child Safety**: Evaluation of text-to-text and image to text prompts
|
||||
covering child safety policies, including child sexual abuse and
|
||||
exploitation.
|
||||
- **Content Safety:** Evaluation of text-to-text and image to text prompts
|
||||
covering safety policies including, harassment, violence and gore, and hate
|
||||
speech.
|
||||
- **Representational Harms**: Evaluation of text-to-text and image to text
|
||||
prompts covering safety policies including bias, stereotyping, and harmful
|
||||
associations or inaccuracies.
|
||||
|
||||
In addition to development level evaluations, we conduct "assurance
|
||||
evaluations" which are our 'arms-length' internal evaluations for responsibility
|
||||
governance decision making. They are conducted separately from the model
|
||||
development team, to inform decision making about release. High level findings
|
||||
are fed back to the model team, but prompt sets are held-out to prevent
|
||||
overfitting and preserve the results' ability to inform decision making.
|
||||
Assurance evaluation results are reported to our Responsibility & Safety Council
|
||||
as part of release review.
|
||||
|
||||
### Evaluation Results
|
||||
|
||||
For all areas of safety testing, we saw major improvements in the categories of
|
||||
child safety, content safety, and representational harms relative to previous
|
||||
Gemma models. All testing was conducted without safety filters to evaluate the
|
||||
model capabilities and behaviors. For both text-to-text and image-to-text, and
|
||||
across all model sizes, the model produced minimal policy violations, and showed
|
||||
significant improvements over previous Gemma models' performance with respect
|
||||
to ungrounded inferences. A limitation of our evaluations was they included only
|
||||
English language prompts.
|
||||
|
||||
## Usage and Limitations
|
||||
|
||||
These models have certain limitations that users should be aware of.
|
||||
|
||||
### Intended Usage
|
||||
|
||||
Open vision-language models (VLMs) models have a wide range of applications
|
||||
across various industries and domains. The following list of potential uses is
|
||||
not comprehensive. The purpose of this list is to provide contextual information
|
||||
about the possible use-cases that the model creators considered as part of model
|
||||
training and development.
|
||||
|
||||
- Content Creation and Communication
|
||||
- Text Generation: These models can be used to generate creative text
|
||||
formats such as poems, scripts, code, marketing copy, and email drafts.
|
||||
- Chatbots and Conversational AI: Power conversational interfaces
|
||||
for customer service, virtual assistants, or interactive applications.
|
||||
- Text Summarization: Generate concise summaries of a text corpus,
|
||||
research papers, or reports.
|
||||
- Image Data Extraction: These models can be used to extract,
|
||||
interpret, and summarize visual data for text communications.
|
||||
- Research and Education
|
||||
- Natural Language Processing (NLP) and VLM Research: These
|
||||
models can serve as a foundation for researchers to experiment with VLM
|
||||
and NLP techniques, develop algorithms, and contribute to the
|
||||
advancement of the field.
|
||||
- Language Learning Tools: Support interactive language learning
|
||||
experiences, aiding in grammar correction or providing writing practice.
|
||||
- Knowledge Exploration: Assist researchers in exploring large
|
||||
bodies of text by generating summaries or answering questions about
|
||||
specific topics.
|
||||
|
||||
### Limitations
|
||||
|
||||
- Training Data
|
||||
- The quality and diversity of the training data significantly
|
||||
influence the model's capabilities. Biases or gaps in the training data
|
||||
can lead to limitations in the model's responses.
|
||||
- The scope of the training dataset determines the subject areas
|
||||
the model can handle effectively.
|
||||
- Context and Task Complexity
|
||||
- Models are better at tasks that can be framed with clear
|
||||
prompts and instructions. Open-ended or highly complex tasks might be
|
||||
challenging.
|
||||
- A model's performance can be influenced by the amount of context
|
||||
provided (longer context generally leads to better outputs, up to a
|
||||
certain point).
|
||||
- Language Ambiguity and Nuance
|
||||
- Natural language is inherently complex. Models might struggle
|
||||
to grasp subtle nuances, sarcasm, or figurative language.
|
||||
- Factual Accuracy
|
||||
- Models generate responses based on information they learned
|
||||
from their training datasets, but they are not knowledge bases. They
|
||||
may generate incorrect or outdated factual statements.
|
||||
- Common Sense
|
||||
- Models rely on statistical patterns in language. They might
|
||||
lack the ability to apply common sense reasoning in certain situations.
|
||||
|
||||
### Ethical Considerations and Risks
|
||||
|
||||
The development of vision-language models (VLMs) raises several ethical
|
||||
concerns. In creating an open model, we have carefully considered the following:
|
||||
|
||||
- Bias and Fairness
|
||||
- VLMs trained on large-scale, real-world text and image data can
|
||||
reflect socio-cultural biases embedded in the training material. These
|
||||
models underwent careful scrutiny, input data pre-processing described
|
||||
and posterior evaluations reported in this card.
|
||||
- Misinformation and Misuse
|
||||
- VLMs can be misused to generate text that is false, misleading,
|
||||
or harmful.
|
||||
- Guidelines are provided for responsible use with the model, see the
|
||||
[Responsible Generative AI Toolkit][rai-toolkit].
|
||||
- Transparency and Accountability:
|
||||
- This model card summarizes details on the models' architecture,
|
||||
capabilities, limitations, and evaluation processes.
|
||||
- A responsibly developed open model offers the opportunity to
|
||||
share innovation by making VLM technology accessible to developers and
|
||||
researchers across the AI ecosystem.
|
||||
|
||||
Risks identified and mitigations:
|
||||
|
||||
- **Perpetuation of biases**: It's encouraged to perform continuous
|
||||
monitoring (using evaluation metrics, human review) and the exploration of
|
||||
de-biasing techniques during model training, fine-tuning, and other use
|
||||
cases.
|
||||
- **Generation of harmful content**: Mechanisms and guidelines for content
|
||||
safety are essential. Developers are encouraged to exercise caution and
|
||||
implement appropriate content safety safeguards based on their specific
|
||||
product policies and application use cases.
|
||||
- **Misuse for malicious purposes**: Technical limitations and developer
|
||||
and end-user education can help mitigate against malicious applications of
|
||||
VLMs. Educational resources and reporting mechanisms for users to flag
|
||||
misuse are provided. Prohibited uses of Gemma models are outlined in the
|
||||
[Gemma Prohibited Use Policy][prohibited-use].
|
||||
- **Privacy violations**: Models were trained on data filtered for removal
|
||||
of certain personal information and other sensitive data. Developers are
|
||||
encouraged to adhere to privacy regulations with privacy-preserving
|
||||
techniques.
|
||||
|
||||
### Benefits
|
||||
|
||||
At the time of release, this family of models provides high-performance open
|
||||
vision-language model implementations designed from the ground up for
|
||||
responsible AI development compared to similarly sized models.
|
||||
|
||||
Using the benchmark evaluation metrics described in this document, these models
|
||||
have shown to provide superior performance to other, comparably-sized open model
|
||||
alternatives.
|
||||
|
||||
[g3-tech-report]: https://goo.gle/Gemma3Report
|
||||
[rai-toolkit]: https://ai.google.dev/responsible
|
||||
[kaggle-gemma]: https://www.kaggle.com/models/google/gemma-3
|
||||
[vertex-mg-gemma3]: https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/gemma3
|
||||
[terms]: https://ai.google.dev/gemma/terms
|
||||
[safety-policies]: https://ai.google/static/documents/ai-responsibility-update-published-february-2025.pdf
|
||||
[prohibited-use]: https://ai.google.dev/gemma/prohibited_use_policy
|
||||
[tpu]: https://cloud.google.com/tpu/docs/intro-to-tpu
|
||||
[sustainability]: https://sustainability.google/operating-sustainably/
|
||||
[jax]: https://github.com/jax-ml/jax
|
||||
[ml-pathways]: https://blog.google/technology/ai/introducing-pathways-next-generation-ai-architecture/
|
||||
[sustainability]: https://sustainability.google/operating-sustainably/
|
||||
[gemini-2-paper]: https://arxiv.org/abs/2312.11805
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
{
|
||||
"<image_soft_token>": 262144
|
||||
}
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
{
|
||||
"chat_template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n {%- if messages[0]['content'] is string -%}\n {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n {%- else -%}\n {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n {%- endif -%}\n {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n {%- set first_user_prefix = \"\" -%}\n {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n {%- endif -%}\n {%- if (message['role'] == 'assistant') -%}\n {%- set role = \"model\" -%}\n {%- else -%}\n {%- set role = message['role'] -%}\n {%- endif -%}\n {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n {%- if message['content'] is string -%}\n {{ message['content'] | trim }}\n {%- elif message['content'] is iterable -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'image' -%}\n {{ '<start_of_image>' }}\n {%- elif item['type'] == 'text' -%}\n {{ item['text'] | trim }}\n {%- endif -%}\n {%- endfor -%}\n {%- else -%}\n {{ raise_exception(\"Invalid content type\") }}\n {%- endif -%}\n {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n {{'<start_of_turn>model\n'}}\n{%- endif -%}\n"
|
||||
}
|
||||
|
|
@ -0,0 +1,38 @@
|
|||
{
|
||||
"architectures": [
|
||||
"Gemma3ForConditionalGeneration"
|
||||
],
|
||||
"boi_token_index": 255999,
|
||||
"eoi_token_index": 256000,
|
||||
"eos_token_id": [
|
||||
1,
|
||||
106
|
||||
],
|
||||
"image_token_index": 262144,
|
||||
"initializer_range": 0.02,
|
||||
"mm_tokens_per_image": 256,
|
||||
"model_type": "gemma3",
|
||||
"text_config": {
|
||||
"hidden_size": 2560,
|
||||
"intermediate_size": 10240,
|
||||
"model_type": "gemma3_text",
|
||||
"num_hidden_layers": 34,
|
||||
"rope_scaling": {
|
||||
"factor": 8.0,
|
||||
"rope_type": "linear"
|
||||
},
|
||||
"sliding_window": 1024
|
||||
},
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.50.0.dev0",
|
||||
"vision_config": {
|
||||
"hidden_size": 1152,
|
||||
"image_size": 896,
|
||||
"intermediate_size": 4304,
|
||||
"model_type": "siglip_vision_model",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 27,
|
||||
"patch_size": 14,
|
||||
"vision_use_head": false
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1 @@
|
|||
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 2,
|
||||
"cache_implementation": "hybrid",
|
||||
"eos_token_id": [
|
||||
1,
|
||||
106
|
||||
],
|
||||
"pad_token_id": 0,
|
||||
"transformers_version": "4.50.0.dev0"
|
||||
}
|
||||
Binary file not shown.
Binary file not shown.
|
|
@ -0,0 +1,890 @@
|
|||
{
|
||||
"metadata": {
|
||||
"total_size": 8600158944
|
||||
},
|
||||
"weight_map": {
|
||||
"language_model.model.embed_tokens.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.14.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.14.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.14.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.14.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.14.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.14.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.14.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.14.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.14.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.14.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.15.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.15.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.16.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.17.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.18.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.19.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.20.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.20.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.21.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.22.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.23.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.24.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.25.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.26.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.27.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.28.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.29.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.30.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.30.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.31.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.32.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.post_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.pre_feedforward_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.33.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"language_model.model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.post_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.pre_feedforward_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"language_model.model.norm.weight": "model-00002-of-00002.safetensors",
|
||||
"multi_modal_projector.mm_input_projection_weight": "model-00001-of-00002.safetensors",
|
||||
"multi_modal_projector.mm_soft_emb_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.embeddings.patch_embedding.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.embeddings.patch_embedding.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.embeddings.position_embedding.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.19.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.20.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.21.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.22.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.23.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.24.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.25.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.26.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.layer_norm1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.layer_norm1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.layer_norm2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.layer_norm2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.self_attn.out_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.self_attn.out_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.post_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"vision_tower.vision_model.post_layernorm.weight": "model-00001-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,29 @@
|
|||
{
|
||||
"do_convert_rgb": null,
|
||||
"do_normalize": true,
|
||||
"do_pan_and_scan": null,
|
||||
"do_rescale": true,
|
||||
"do_resize": true,
|
||||
"image_mean": [
|
||||
0.5,
|
||||
0.5,
|
||||
0.5
|
||||
],
|
||||
"image_processor_type": "Gemma3ImageProcessor",
|
||||
"image_seq_length": 256,
|
||||
"image_std": [
|
||||
0.5,
|
||||
0.5,
|
||||
0.5
|
||||
],
|
||||
"pan_and_scan_max_num_crops": null,
|
||||
"pan_and_scan_min_crop_size": null,
|
||||
"pan_and_scan_min_ratio_to_activate": null,
|
||||
"processor_class": "Gemma3Processor",
|
||||
"resample": 2,
|
||||
"rescale_factor": 0.00392156862745098,
|
||||
"size": {
|
||||
"height": 896,
|
||||
"width": 896
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
{
|
||||
"image_seq_length": 256,
|
||||
"processor_class": "Gemma3Processor"
|
||||
}
|
||||
|
|
@ -0,0 +1,33 @@
|
|||
{
|
||||
"boi_token": "<start_of_image>",
|
||||
"bos_token": {
|
||||
"content": "<bos>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eoi_token": "<end_of_image>",
|
||||
"eos_token": {
|
||||
"content": "<eos>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"image_token": "<image_soft_token>",
|
||||
"pad_token": {
|
||||
"content": "<pad>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
Binary file not shown.
File diff suppressed because it is too large
Load Diff
Loading…
Reference in New Issue