diff --git a/README.md b/README.md index b82ef4b..9af3a60 100644 --- a/README.md +++ b/README.md @@ -11,6 +11,7 @@ Read this in [English](README_en.md) ## 项目更新 +- 🔥🔥 **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 - 🔥🔥 **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) - 🔥 **News**: ```2024/10/12```: 增加了 GLM-4v-9B 模型对vllm框架的支持 - 🔥 **News**: ```2024/09/06```: 增加了在 GLM-4v-9B 模型上构建OpenAI API兼容的服务端 @@ -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 ## Model List -| Model | Type | Seq Length | Download | Online Demo | -|------------------|------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| 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) | / | -| 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)
[🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) | -| 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) | / | -| 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) | +| Model | Type | Seq Length | Transformers | vLLM | Download | Online Demo | +|:-------------------:|:----:|:----------:|:------------:|:--------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| GLM-4-9B | Base | 8K | <= 4.45 | <= 0.6.2 | [🤗 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) | / | +| GLM-4-9B-Chat | Chat | 128K | <= 4.45 | <= 0.6.2 | [🤗 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)
[🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) | +| GLM-4-9B-Chat-HF | Chat | 128K | >= 4.46 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-hf)
[🤖 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)
[🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) | +| GLM-4-9B-Chat-1M | Chat | 1M | <= 4.45 | <= 0.6.2 | [🤗 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) | / | +| GLM-4-9B-Chat-1M-HF | Chat | 1M | >= 4.46 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-1m-hf)
[🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-1m-hf) | / | +| GLM-4V-9B | Chat | 8K | >= 4.46 | >= 0.6.3 | [🤗 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) | ## 评测结果 @@ -151,7 +154,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer import os 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 -MODEL_PATH = "THUDM/glm-4-9b-chat" +MODEL_PATH = "THUDM/glm-4-9b-chat-hf" device = "cuda" if torch.cuda.is_available() else "cpu" @@ -192,7 +195,7 @@ from vllm import LLM, SamplingParams # max_model_len, tp_size = 1048576, 4 # 如果遇见 OOM 现象，建议减少max_model_len，或者增加tp_size max_model_len, tp_size = 131072, 1 -model_name = "THUDM/glm-4-9b-chat" +model_name = "THUDM/glm-4-9b-chat-hf" prompt = [{"role": "user", "content": "你好"}] tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) @@ -290,7 +293,7 @@ for o in outputs: ## 完整项目列表 -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 +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 + [basic_demo](basic_demo/README.md): 在这里包含了 + 使用 transformers 和 vLLM 后端的交互代码 diff --git a/README_en.md b/README_en.md index 4719a3e..9f4cd42 100644 --- a/README_en.md +++ b/README_en.md @@ -8,7 +8,7 @@

## Update - +- 🔥🔥 **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 - 🔥🔥 **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). - 🔥 **News**: ```2024/10/12```: Add GLM-4v-9B model support for vllm framework. - 🔥 **News**: ```2024/09/06```: Add support for OpenAI API server on the GLM-4v-9B model. @@ -67,14 +67,17 @@ GPT-4-turbo-2024-04-09, Gemini 1.0 Pro, Qwen-VL-Max, and Claude 3 Opus. ## Model List -| Model | Type | Seq Length | Download | Online Demo | -|------------------|------|------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| 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) | / | -| 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)
[🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) | -| 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) | / | -| 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) | +| Model | Type | Seq Length | Transformers | vLLM | Download | Online Demo | +|:-------------------:|:----:|:----------:|:------------:|:--------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| GLM-4-9B | Base | 8K | <= 4.45 | <= 0.6.2 | [🤗 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) | / | +| GLM-4-9B-Chat | Chat | 128K | <= 4.45 | <= 0.6.2 | [🤗 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)
[🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) | +| GLM-4-9B-Chat-HF | Chat | 128K | >= 4.46 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-hf)
[🤖 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)
[🤖 ModelScope vLLM](https://modelscope.cn/studios/ZhipuAI/glm-4-9b-chat-vllm/summary) | +| GLM-4-9B-Chat-1M | Chat | 1M | <= 4.45 | <= 0.6.2 | [🤗 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) | / | +| GLM-4-9B-Chat-1M-HF | Chat | 1M | >= 4.46 | <= 0.6.2 | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-9b-chat-1m-hf)
[🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-9b-chat-1m-hf) | / | +| GLM-4V-9B | Chat | 8K | >= 4.46 | >= 0.6.3 | [🤗 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) | -## BenchMark + +## BenchMarkß ### Typical Tasks @@ -168,7 +171,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer import os os.environ['CUDA_VISIBLE_DEVICES'] = '0' # Set the GPU number. If inference with multiple GPUs, set multiple GPU numbers -MODEL_PATH = "THUDM/glm-4-9b-chat" +MODEL_PATH = "THUDM/glm-4-9b-chat-hf" device = "cuda" if torch.cuda.is_available() else "cpu" @@ -208,7 +211,7 @@ from vllm import LLM, SamplingParams # GLM-4-9B-Chat # If you encounter OOM, you can try to reduce max_model_len or increase tp_size max_model_len, tp_size = 131072, 1 -model_name = "THUDM/glm-4-9b-chat" +model_name = "THUDM/glm-4-9b-chat-hf" prompt = [{"role": "user", "content": "你好"}] tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) diff --git a/basic_demo/glm4v_server.py b/basic_demo/glm4v_server.py index cffa944..549f661 100644 --- a/basic_demo/glm4v_server.py +++ b/basic_demo/glm4v_server.py @@ -302,7 +302,10 @@ def generate_stream_glm4v(model: AutoModel, tokenizer: AutoTokenizer, params: di inputs.append({"role": "user", "content": user_msg}) if model_msg: inputs.append({"role": "assistant", "content": model_msg}) - inputs.append({"role": "user", "content": query, "image": image_list[0]}) + if len(image_list) >= 1: + inputs.append({"role": "user", "content": query, "image": image_list[0]}) + else: + inputs.append({"role": "user", "content": query}) model_inputs = tokenizer.apply_chat_template( inputs, diff --git a/basic_demo/glm_server.py b/basic_demo/glm_server.py index 2ae8b22..d975dea 100644 --- a/basic_demo/glm_server.py +++ b/basic_demo/glm_server.py @@ -207,9 +207,6 @@ async def generate_stream_glm4(params): "top_p": top_p, "top_k": -1, "repetition_penalty": repetition_penalty, - "use_beam_search": False, - "length_penalty": 1, - "early_stopping": False, "stop_token_ids": [151329, 151336, 151338], "ignore_eos": False, "max_tokens": max_new_tokens, @@ -218,7 +215,7 @@ async def generate_stream_glm4(params): "skip_special_tokens": True, } sampling_params = SamplingParams(**params_dict) - async for output in engine.generate(inputs=inputs, sampling_params=sampling_params, request_id=f"{time.time()}"): + async for output in engine.generate(prompt=inputs, sampling_params=sampling_params, request_id=f"{time.time()}"): output_len = len(output.outputs[0].token_ids) input_len = len(output.prompt_token_ids) ret = { diff --git a/basic_demo/openai_api_request.py b/basic_demo/openai_api_request.py index 92bee35..f1c7fab 100644 --- a/basic_demo/openai_api_request.py +++ b/basic_demo/openai_api_request.py @@ -95,12 +95,12 @@ def function_chat(use_stream=False): def simple_chat(use_stream=False): messages = [ { - "role": "system", + "role": "user", "content": "请在你输出的时候都带上“喵喵喵”三个字，放在开头。", }, { "role": "user", - "content": "你是谁" + "content": "你是猫吗" } ] response = client.chat.completions.create( @@ -201,7 +201,12 @@ def glm4v_simple_image_chat(use_stream=False, img_path=None): if __name__ == "__main__": - simple_chat(use_stream=False) - # function_chat(use_stream=False) - # glm4v_simple_image_chat(use_stream=False, img_path="demo.jpg") + # Testing the text model + simple_chat(use_stream=False) + + # Testing the text model with tools + # function_chat(use_stream=False) + + # Testing images of multimodal models + # glm4v_simple_image_chat(use_stream=False, img_path="demo.jpg") diff --git a/basic_demo/requirements.txt b/basic_demo/requirements.txt index 4ff1483..cad81ed 100644 --- a/basic_demo/requirements.txt +++ b/basic_demo/requirements.txt @@ -10,14 +10,14 @@ tiktoken>=0.7.0 numpy==1.26.4 # Need less than 2.0.0 accelerate>=1.0.1 sentence_transformers>=3.1.1 -gradio>=4.44.1 # web demo +gradio==4.44.1 # web demo openai>=1.51.0 # openai demo einops>=0.8.0 pillow>=10.4.0 sse-starlette>=2.1.3 bitsandbytes>=0.43.3 # INT4 Loading -# vllm>=0.6.4 # using with VLLM Framework +# vllm>=0.6.3 # using with VLLM Framework # flash-attn>=2.6.3 # using with flash-attention 2 # PEFT model, not need if you don't use PEFT finetune model. # peft>=0.13.0 # Using with finetune model \ No newline at end of file diff --git a/basic_demo/trans_cli_vision_demo.py b/basic_demo/trans_cli_vision_demo.py index 30a78d2..adca35d 100644 --- a/basic_demo/trans_cli_vision_demo.py +++ b/basic_demo/trans_cli_vision_demo.py @@ -29,6 +29,8 @@ tokenizer = AutoTokenizer.from_pretrained( trust_remote_code=True, encode_special_tokens=True ) + +## For BF16 inference model = AutoModel.from_pretrained( MODEL_PATH, trust_remote_code=True, @@ -37,7 +39,6 @@ model = AutoModel.from_pretrained( device_map="auto", ).eval() - ## For INT4 inference # model = AutoModel.from_pretrained( # MODEL_PATH, diff --git a/basic_demo/trans_web_demo.py b/basic_demo/trans_web_demo.py index 1a470de..2d8e35a 100644 --- a/basic_demo/trans_web_demo.py +++ b/basic_demo/trans_web_demo.py @@ -3,6 +3,9 @@ This script creates an interactive web demo for the GLM-4-9B model using Gradio, a Python library for building quick and easy UI components for machine learning models. It's designed to showcase the capabilities of the GLM-4-9B model in a user-friendly interface, allowing users to interact with the model through a chat-like interface. + +Note: + Using with glm-4-9b-chat-hf will require `transformers>=4.46.0". """ import os @@ -27,7 +30,7 @@ from transformers import ( ModelType = Union[PreTrainedModel, PeftModelForCausalLM] TokenizerType = Union[PreTrainedTokenizer, PreTrainedTokenizerFast] -MODEL_PATH = os.environ.get('MODEL_PATH', 'THUDM/glm-4-9b-chat') +MODEL_PATH = os.environ.get('MODEL_PATH', 'THUDM/glm-4-9b-chat-hf') TOKENIZER_PATH = os.environ.get("TOKENIZER_PATH", MODEL_PATH) diff --git a/basic_demo/trans_web_vision_demo.py b/basic_demo/trans_web_vision_demo.py index 05d1563..91d9875 100644 --- a/basic_demo/trans_web_vision_demo.py +++ b/basic_demo/trans_web_vision_demo.py @@ -7,7 +7,7 @@ Usage: Requirements: - Gradio package - - Type `pip install gradio` to install Gradio. + - Type `pip install gradio==4.44.1` to install Gradio. """ import os @@ -18,7 +18,7 @@ from transformers import ( AutoTokenizer, StoppingCriteria, StoppingCriteriaList, - TextIteratorStreamer, AutoModel, BitsAndBytesConfig + TextIteratorStreamer, AutoModel ) from PIL import Image import requests