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mlx inference
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.gitignore
vendored
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.gitignore
vendored
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*.pyc
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finetune/output/*
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wip.*
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.idea
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venv
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.venv
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.env
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@ -488,6 +488,12 @@ python demo/vllm_based_demo.py --model_path <vllmcpm_repo_path>
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python demo/hf_based_demo.py --model_path <hf_repo_path>
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```
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#### 使用如下命令启动基于 Mac mlx 加速框架推理
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你需要安装 `mlx_lm` 库,并且,你需要下载对应的转换后的专用模型权重[MiniCPM-2B-sft-bf16-llama-format-mlx](https://huggingface.co/mlx-community/MiniCPM-2B-sft-bf16-llama-format-mlx),然后运行以下命令:
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```shell
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python -m mlx_lm.generate --model mlx-community/MiniCPM-2B-sft-bf16-llama-format-mlx --prompt "hello, tell me a joke." --trust-remote-code
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```
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<p id="6"></p>
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demo/mlx_based_demo.py
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demo/mlx_based_demo.py
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"""
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使用 MLX 快速推理 MiniCPM
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如果你使用 Mac 设备进行推理,可以直接使用MLX进行推理。
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由于 MiniCPM 暂时不支持 mlx 格式转换。您可以下载由 MLX 社群转换好的模型 [MiniCPM-2B-sft-bf16-llama-format-mlx](https://huggingface.co/mlx-community/MiniCPM-2B-sft-bf16-llama-format-mlx)。
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并安装对应的依赖包
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```bash
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pip install mlx-lm
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```
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这是一个简单的推理代码,使用 Mac 设备推理 MiniCPM-2
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```python
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python -m mlx_lm.generate --model mlx-community/MiniCPM-2B-sft-bf16-llama-format-mlx --prompt "hello, tell me a joke." --trust-remote-code
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```
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"""
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from mlx_lm import load, generate
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from jinja2 import Template
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def chat_with_model():
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model, tokenizer = load("mlx-community/MiniCPM-2B-sft-bf16-llama-format-mlx")
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print("Model loaded. Start chatting! (Type 'quit' to stop)")
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messages = []
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chat_template = Template(
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"{% for message in messages %}{% if message['role'] == 'user' %}{{'<用户>' + message['content'].strip() + '<AI>'}}{% else %}{{message['content'].strip()}}{% endif %}{% endfor %}")
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while True:
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user_input = input("You: ")
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if user_input.lower() == 'quit':
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break
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messages.append({"role": "user", "content": user_input})
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response = generate(model, tokenizer, prompt=chat_template.render(messages=messages), verbose=True)
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print("Model:", response)
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messages.append({"role": "ai", "content": response})
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chat_with_model()
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requirements.txt
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requirements.txt
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transformers>=4.38.2
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torch>=2.0.0
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triton>=2.2.0
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httpx>=0.27.0
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gradio>=4.21.0
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flash_attn>=2.4.1
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accelerate>=0.28.0
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sentence_transformers>=2.6.0
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sse_starlette>=2.0.0
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tiktoken>=0.6.0
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mlx_lm>=0.5.0
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