Merge pull request #634 from sixsixcoder/main
Support for GLM-4-9B-Chat-hf and GLM-4v-9B models on vLLM >= 0.6.3 and transformers >= 4.46.0
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Yuxuan.Zhang
GitHub
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21
README.md
21
README.md
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@ -11,6 +11,7 @@ Read this in [English](README_en.md)
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## 项目更新
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- 🔥🔥 **News**: ```2024/11/01```: 支持了 GLM-4-9B-Chat-hf 和 GLM-4v-9B 模型在 vLLM 0.6.3 以上版本和 transformers 4.46.0 以上版本运行
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- 🔥🔥 **News**: ```2024/10/25```: 我们开源了端到端中英语音对话模型 [GLM-4-Voice](https://github.com/THUDM/GLM-4-Voice)
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- 🔥 **News**: ```2024/10/12```: 增加了 GLM-4v-9B 模型对vllm框架的支持
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- 🔥 **News**: ```2024/09/06```: 增加了在 GLM-4v-9B 模型上构建OpenAI API兼容的服务端
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@ -54,12 +55,14 @@ GLM-4V-9B。**GLM-4V-9B** 具备 1120 * 1120 高分辨率下的中英双语多
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## Model List
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| Model | Type | Seq Length | Download | Online Demo |
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|------------------|------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| GLM-4-9B | Base | 8K | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b) [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/glm-4-9b) | / |
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| GLM-4-9B-Chat | Chat | 128K | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat) [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B-Chat) | [🤖 ModelScope CPU](https://modelscope.cn/studios/dash-infer/GLM-4-Chat-DashInfer-Demo/summary)<br> [🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) |
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| GLM-4-9B-Chat-1M | Chat | 1M | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-1m) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-1m) [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B-Chat-1M) | / |
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| GLM-4V-9B | Chat | 8K | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4v-9b) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4v-9b) [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4V-9B ) | [🤖 ModelScope](https://modelscope.cn/studios/ZhipuAI/glm-4v-9b-Demo/summary) |
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| Model | Type | Seq Length | Transformers | vLLM | Download | Online Demo |
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|:-------------------:|:----:|:----------:|:------------:|:--------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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| GLM-4-9B | Base | 8K | <= 4.45 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b)<br> [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/glm-4-9b) | / |
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| GLM-4-9B-Chat | Chat | 128K | <= 4.45 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat)<br> [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B-Chat) | [🤖 ModelScope CPU](https://modelscope.cn/studios/dash-infer/GLM-4-Chat-DashInfer-Demo/summary)<br> [🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) |
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| GLM-4-9B-Chat-HF | Chat | 128K | >= 4.46 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-hf)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-hf) | [🤖 ModelScope CPU](https://modelscope.cn/studios/dash-infer/GLM-4-Chat-DashInfer-Demo/summary)<br> [🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) |
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| GLM-4-9B-Chat-1M | Chat | 1M | <= 4.45 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-1m)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-1m)<br> [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B-Chat-1M) | / |
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| GLM-4-9B-Chat-1M-HF | Chat | 1M | >= 4.46 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-1m-hf)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-1m-hf) | / |
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| GLM-4V-9B | Chat | 8K | >= 4.46 | >= 0.6.3 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4v-9b)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4v-9b)<br> [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4V-9B) | [🤖 ModelScope](https://modelscope.cn/studios/ZhipuAI/glm-4v-9b-Demo/summary) |
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## 评测结果
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@ -151,7 +154,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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import os
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os.environ['CUDA_VISIBLE_DEVICES'] = '0' # 设置 GPU 编号，如果单机单卡指定一个，单机多卡指定多个 GPU 编号
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MODEL_PATH = "THUDM/glm-4-9b-chat"
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MODEL_PATH = "THUDM/glm-4-9b-chat-hf"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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@ -192,7 +195,7 @@ from vllm import LLM, SamplingParams
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# max_model_len, tp_size = 1048576, 4
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# 如果遇见 OOM 现象，建议减少max_model_len，或者增加tp_size
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max_model_len, tp_size = 131072, 1
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model_name = "THUDM/glm-4-9b-chat"
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model_name = "THUDM/glm-4-9b-chat-hf"
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prompt = [{"role": "user", "content": "你好"}]
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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@ -290,7 +293,7 @@ for o in outputs:
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## 完整项目列表
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如果你想更进一步了解 GLM-4-9B 系列开源模型，本开源仓库通过以下内容为开发者提供基础的 GLM-4-9B的使用和开发代码
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如果你想更进一步了解 GLM-4-9B 系列开源模型，本开源仓库通过以下内容为开发者提供基础的 GLM-4-9B 的使用和开发代码
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+ [basic_demo](basic_demo/README.md): 在这里包含了
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+ 使用 transformers 和 vLLM 后端的交互代码
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23
README_en.md
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README_en.md
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@ -8,7 +8,7 @@
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</p>
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## Update
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- 🔥🔥 **News**: ```2024/11/01```: Support for GLM-4-9B-Chat-hf and GLM-4v-9B models on vLLM >= 0.6.3 and transformers >= 4.46.0
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- 🔥🔥 **News**: ```2024/10/25```: We have open-sourced the end-to-end Chinese-English voice dialogue model [GLM-4-Voice](https://github.com/THUDM/GLM-4-Voice).
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- 🔥 **News**: ```2024/10/12```: Add GLM-4v-9B model support for vllm framework.
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- 🔥 **News**: ```2024/09/06```: Add support for OpenAI API server on the GLM-4v-9B model.
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@ -67,14 +67,17 @@ GPT-4-turbo-2024-04-09, Gemini 1.0 Pro, Qwen-VL-Max, and Claude 3 Opus.
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## Model List
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| Model | Type | Seq Length | Download | Online Demo |
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|------------------|------|------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| GLM-4-9B | Base | 8K | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b) [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B) | / |
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| GLM-4-9B-Chat | Chat | 128K | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat) [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B-Chat) | [🤖 ModelScope CPU](https://modelscope.cn/studios/dash-infer/GLM-4-Chat-DashInfer-Demo/summary)<br> [🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) |
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| GLM-4-9B-Chat-1M | Chat | 1M | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-1m) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-1m) [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B-Chat-1M) | / |
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| GLM-4V-9B | Chat | 8K | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4v-9b) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4v-9b) [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4V-9B) | [🤖 ModelScope](https://modelscope.cn/studios/ZhipuAI/glm-4v-9b-Demo/summary) |
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| Model | Type | Seq Length | Transformers | vLLM | Download | Online Demo |
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|:-------------------:|:----:|:----------:|:------------:|:--------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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| GLM-4-9B | Base | 8K | <= 4.45 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b)<br> [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/glm-4-9b) | / |
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| GLM-4-9B-Chat | Chat | 128K | <= 4.45 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat)<br> [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B-Chat) | [🤖 ModelScope CPU](https://modelscope.cn/studios/dash-infer/GLM-4-Chat-DashInfer-Demo/summary)<br> [🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) |
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| GLM-4-9B-Chat-HF | Chat | 128K | >= 4.46 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-hf)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-hf) | [🤖 ModelScope CPU](https://modelscope.cn/studios/dash-infer/GLM-4-Chat-DashInfer-Demo/summary)<br> [🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) |
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| GLM-4-9B-Chat-1M | Chat | 1M | <= 4.45 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-1m)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-1m)<br> [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4-9B-Chat-1M) | / |
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| GLM-4-9B-Chat-1M-HF | Chat | 1M | >= 4.46 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-1m-hf)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-1m-hf) | / |
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| GLM-4V-9B | Chat | 8K | >= 4.46 | >= 0.6.3 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4v-9b)<br> [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4v-9b)<br> [🟣 WiseModel](https://wisemodel.cn/models/ZhipuAI/GLM-4V-9B) | [🤖 ModelScope](https://modelscope.cn/studios/ZhipuAI/glm-4v-9b-Demo/summary) |
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## BenchMark
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## BenchMarkß
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### Typical Tasks
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@ -168,7 +171,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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import os
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os.environ['CUDA_VISIBLE_DEVICES'] = '0' # Set the GPU number. If inference with multiple GPUs, set multiple GPU numbers
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MODEL_PATH = "THUDM/glm-4-9b-chat"
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MODEL_PATH = "THUDM/glm-4-9b-chat-hf"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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@ -208,7 +211,7 @@ from vllm import LLM, SamplingParams
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# GLM-4-9B-Chat
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# If you encounter OOM, you can try to reduce max_model_len or increase tp_size
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max_model_len, tp_size = 131072, 1
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model_name = "THUDM/glm-4-9b-chat"
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model_name = "THUDM/glm-4-9b-chat-hf"
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prompt = [{"role": "user", "content": "你好"}]
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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@ -302,7 +302,10 @@ def generate_stream_glm4v(model: AutoModel, tokenizer: AutoTokenizer, params: di
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inputs.append({"role": "user", "content": user_msg})
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if model_msg:
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inputs.append({"role": "assistant", "content": model_msg})
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if len(image_list) >= 1:
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inputs.append({"role": "user", "content": query, "image": image_list[0]})
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else:
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inputs.append({"role": "user", "content": query})
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model_inputs = tokenizer.apply_chat_template(
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inputs,
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@ -207,9 +207,6 @@ async def generate_stream_glm4(params):
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"top_p": top_p,
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"top_k": -1,
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"repetition_penalty": repetition_penalty,
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"use_beam_search": False,
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"length_penalty": 1,
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"early_stopping": False,
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"stop_token_ids": [151329, 151336, 151338],
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"ignore_eos": False,
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"max_tokens": max_new_tokens,
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@ -218,7 +215,7 @@ async def generate_stream_glm4(params):
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"skip_special_tokens": True,
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}
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sampling_params = SamplingParams(**params_dict)
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async for output in engine.generate(inputs=inputs, sampling_params=sampling_params, request_id=f"{time.time()}"):
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async for output in engine.generate(prompt=inputs, sampling_params=sampling_params, request_id=f"{time.time()}"):
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output_len = len(output.outputs[0].token_ids)
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input_len = len(output.prompt_token_ids)
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ret = {
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@ -95,12 +95,12 @@ def function_chat(use_stream=False):
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def simple_chat(use_stream=False):
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messages = [
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{
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"role": "system",
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"role": "user",
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"content": "请在你输出的时候都带上“喵喵喵”三个字，放在开头。",
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},
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{
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"role": "user",
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"content": "你是谁"
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"content": "你是猫吗"
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}
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]
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response = client.chat.completions.create(
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if __name__ == "__main__":
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# Testing the text model
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simple_chat(use_stream=False)
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# Testing the text model with tools
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# function_chat(use_stream=False)
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# Testing images of multimodal models
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# glm4v_simple_image_chat(use_stream=False, img_path="demo.jpg")
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@ -10,14 +10,14 @@ tiktoken>=0.7.0
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numpy==1.26.4 # Need less than 2.0.0
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accelerate>=1.0.1
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sentence_transformers>=3.1.1
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gradio>=4.44.1 # web demo
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gradio==4.44.1 # web demo
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openai>=1.51.0 # openai demo
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einops>=0.8.0
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pillow>=10.4.0
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sse-starlette>=2.1.3
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bitsandbytes>=0.43.3 # INT4 Loading
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# vllm>=0.6.4 # using with VLLM Framework
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# vllm>=0.6.3 # using with VLLM Framework
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# flash-attn>=2.6.3 # using with flash-attention 2
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# PEFT model, not need if you don't use PEFT finetune model.
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# peft>=0.13.0 # Using with finetune model
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@ -29,6 +29,8 @@ tokenizer = AutoTokenizer.from_pretrained(
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trust_remote_code=True,
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encode_special_tokens=True
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)
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## For BF16 inference
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model = AutoModel.from_pretrained(
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MODEL_PATH,
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trust_remote_code=True,
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@ -37,7 +39,6 @@ model = AutoModel.from_pretrained(
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device_map="auto",
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).eval()
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## For INT4 inference
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# model = AutoModel.from_pretrained(
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# MODEL_PATH,
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@ -3,6 +3,9 @@ This script creates an interactive web demo for the GLM-4-9B model using Gradio,
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a Python library for building quick and easy UI components for machine learning models.
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It's designed to showcase the capabilities of the GLM-4-9B model in a user-friendly interface,
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allowing users to interact with the model through a chat-like interface.
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Note:
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Using with glm-4-9b-chat-hf will require `transformers>=4.46.0".
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"""
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import os
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@ -27,7 +30,7 @@ from transformers import (
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ModelType = Union[PreTrainedModel, PeftModelForCausalLM]
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TokenizerType = Union[PreTrainedTokenizer, PreTrainedTokenizerFast]
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MODEL_PATH = os.environ.get('MODEL_PATH', 'THUDM/glm-4-9b-chat')
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MODEL_PATH = os.environ.get('MODEL_PATH', 'THUDM/glm-4-9b-chat-hf')
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TOKENIZER_PATH = os.environ.get("TOKENIZER_PATH", MODEL_PATH)
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@ -7,7 +7,7 @@ Usage:
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Requirements:
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- Gradio package
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- Type `pip install gradio` to install Gradio.
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- Type `pip install gradio==4.44.1` to install Gradio.
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"""
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import os
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@ -18,7 +18,7 @@ from transformers import (
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AutoTokenizer,
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StoppingCriteria,
|
||||
StoppingCriteriaList,
|
||||
TextIteratorStreamer, AutoModel, BitsAndBytesConfig
|
||||
TextIteratorStreamer, AutoModel
|
||||
)
|
||||
from PIL import Image
|
||||
import requests
|
||||
|
|
|
|||
Loading…
Reference in New Issue