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# aya-vision-8b
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---
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inference: false
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library_name: transformers
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language:
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- en
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- fr
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- de
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- es
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- it
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- pt
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- ja
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- ko
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- zh
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- ar
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- el
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- fa
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- pl
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- id
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- cs
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- he
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- hi
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- nl
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- ro
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- ru
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- tr
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- uk
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- vi
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license: cc-by-nc-4.0
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extra_gated_prompt: >-
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By submitting this form, you agree to the [License
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Agreement](https://cohere.com/c4ai-cc-by-nc-license) and acknowledge that the
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information you provide will be collected, used, and shared in accordance with
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Cohere’s [Privacy Policy]( https://cohere.com/privacy). You’ll receive email
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updates about C4AI and Cohere research, events, products and services. You can
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unsubscribe at any time.
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extra_gated_fields:
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Name: text
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Affiliation: text
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Country: country
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I agree to use this model for non-commercial use ONLY: checkbox
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pipeline_tag: image-text-to-text
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---
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aya-vision-8b
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# Model Card for Aya Vision 8B
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<img src="aya-vision-8B.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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**C4AI Aya Vision 8B** is an open weights research release of an 8-billion parameter model with advanced capabilities optimized for a variety of vision-language use cases, including OCR, captioning, visual reasoning, summarization, question answering, code, and more.
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It is a multilingual model trained to excel in 23 languages in vision and language.
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This model card corresponds to the 8-billion version of the Aya Vision model. We also released a 32-billion version which you can find [here](https://huggingface.co/CohereForAI/aya-vision-32B).
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- Developed by: [Cohere For AI](https://cohere.for.ai/)
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- Point of Contact: Cohere For AI: [cohere.for.ai](https://cohere.for.ai/)
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- License: [CC-BY-NC](https://cohere.com/c4ai-cc-by-nc-license), requires also adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy)
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- Model: c4ai-aya-vision-8b
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- Model Size: 8 billion parameters
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- Context length: 16K
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## Try it: Aya Vision in Action
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Before downloading the weights, you can try Aya Vision chat in the [Cohere playground](https://dashboard.cohere.com/playground/chat) or our dedicated [Hugging Face Space](https://huggingface.co/spaces/CohereForAI/aya_expanse) for interactive exploration.
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## WhatsApp Integration
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You can also talk to Aya Vision through the popular messaging service WhatsApp. Use this [link](https://wa.me/14313028498) to open a WhatsApp chatbox with Aya Vision.
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If you don’t have WhatsApp downloaded on your machine you might need to do that, or, if you have it on your phone, you can follow the on-screen instructions to link your phone and WhatsApp Web.
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By the end, you should see a text window which you can use to chat with the model.
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More details about our WhatsApp integration are available [here](https://docs.cohere.com/v2/docs/aya#aya-expanse-integration-with-whatsapp).
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## Example Notebook
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You can also check out the following [notebook](https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/aya_vision_intro.ipynb) to understand how to use Aya Vision for different use cases.
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## How to Use Aya Vision
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Please install `transformers` from the source repository that includes the necessary changes for this model:
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```python
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# pip install 'git+https://github.com/huggingface/transformers.git@v4.49.0-AyaVision'
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from transformers import AutoProcessor, AutoModelForImageTextToText
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import torch
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model_id = "CohereForAI/aya-vision-8b"
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processor = AutoProcessor.from_pretrained(model_id)
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model = AutoModelForImageTextToText.from_pretrained(
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model_id, device_map="auto", torch_dtype=torch.float16
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)
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# Format message with the aya-vision chat template
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messages = [
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{"role": "user",
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"content": [
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{"type": "image", "url": "https://pbs.twimg.com/media/Fx7YvfQWYAIp6rZ?format=jpg&name=medium"},
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{"type": "text", "text": "चित्र में लिखा पाठ क्या कहता है?"},
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]},
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]
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inputs = processor.apply_chat_template(
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messages, padding=True, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt"
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).to(model.device)
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gen_tokens = model.generate(
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**inputs,
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max_new_tokens=300,
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do_sample=True,
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temperature=0.3,
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)
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print(processor.tokenizer.decode(gen_tokens[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
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```
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You can also use the model directly using transformers `pipeline` abstraction:
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```python
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from transformers import pipeline
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pipe = pipeline(model="CohereForAI/aya-vision-8b", task="image-text-to-text", device_map="auto")
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# Format message with the aya-vision chat template
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messages = [
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{"role": "user",
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"content": [
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{"type": "image", "url": "https://media.istockphoto.com/id/458012057/photo/istanbul-turkey.jpg?s=612x612&w=0&k=20&c=qogAOVvkpfUyqLUMr_XJQyq-HkACXyYUSZbKhBlPrxo="},
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{"type": "text", "text": "Bu resimde hangi anıt gösterilmektedir?"},
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]},
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]
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outputs = pipe(text=messages, max_new_tokens=300, return_full_text=False)
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print(outputs)
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```
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## Model Details
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**Input:** Model accepts input text and images.
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**Output:** Model generates text.
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**Model Architecture:** This is a vision-language model that uses a multilingual language model based on [C4AI Command R7B](https://huggingface.co/CohereForAI/c4ai-command-r7b-12-2024) and further post-trained with the [Aya Expanse recipe](https://arxiv.org/abs/2412.04261), paired with [SigLIP2-patch14-384](https://huggingface.co/google/siglip2-so400m-patch14-384) vision encoder through a multimodal adapter for vision-language understanding.
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**Image Processing:** We use **169 visual tokens** to encode an image tile with a resolution of **364x364 pixels**. Input images of arbitrary sizes are mapped to the nearest supported resolution based on the aspect ratio. Aya Vision uses up to 12 input tiles and a thumbnail (resized to 364x364) (2197 image tokens).
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**Languages covered:** The model has been trained on 23 languages: English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Arabic, Chinese (Simplified and Traditional), Russian, Polish, Turkish, Vietnamese, Dutch, Czech, Indonesian, Ukrainian, Romanian, Greek, Hindi, Hebrew, and Persian.
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**Context length**: Aya Vision 8B supports a context length of 16K.
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For more details about how the model was trained, check out [our blogpost](https://huggingface.co/blog/aya-vision).
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## Evaluation
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We evaluated Aya Vision 8B against [Pangea 7B](https://huggingface.co/neulab/Pangea-7B), [Llama-3.2 11B Vision](https://huggingface.co/meta-llama/Llama-3.2-11B-Vision), [Molmo-D 7B](https://huggingface.co/allenai/Molmo-7B-D-0924), [Qwen2.5-VL 7B](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct), [Pixtral 12B](https://huggingface.co/mistralai/Pixtral-12B-2409), and [Gemini Flash 1.5 8B](https://developers.googleblog.com/en/gemini-15-flash-8b-is-now-generally-available-for-use/) using [Aya Vision Benchmark](https://huggingface.co/datasets/CohereForAI/AyaVisionBench) and [m-WildVision](https://huggingface.co/datasets/CohereForAI/m-WildVision).
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Win-rates were determined using claude-3-7-sonnet-20250219 as a judge, based on the superior judge performance compared to other models.
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We also evaluated Aya Vision 8B’s performance for text-only input against the same models using [m-ArenaHard](https://huggingface.co/datasets/CohereForAI/m-ArenaHard), a challenging open-ended generation evaluation, measured using win-rates using gpt-4o-2024-11-20 as a judge.
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<!-- <img src="Aya_Vision_8B_Combined_Win_Rates.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/> -->
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<img src="AyaVision8BWinRates(AyaVisionBench).png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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<img src="AyaVision8BWinRates(m-WildVision).png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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<img src="Aya_Vision_8BvsPangea(AyaVisionBench).png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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<img src="EfficiencyvsPerformance.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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### Model Card Contact
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For errors or additional questions about details in this model card, contact info@for.ai.
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### Terms of Use
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We hope that the release of this model will make community-based research efforts more accessible by releasing the weights of a highly performant 8 billion parameter Vision-Language Model to researchers all over the world.
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This model is governed by a [CC-BY-NC](https://cohere.com/c4ai-cc-by-nc-license) License with an acceptable use addendum, and also requires adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy).
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