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README.md
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---
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library_name: mlc-llm
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base_model: meta-llama/Meta-Llama-3-8B-Instruct
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tags:
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- mlc-llm
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- web-llm
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---
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# Llama-3-8B-Instruct-q0f32-MLC
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This is the [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) model in MLC format `q0f32`.
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The model can be used for projects [MLC-LLM](https://github.com/mlc-ai/mlc-llm) and [WebLLM](https://github.com/mlc-ai/web-llm).
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## Example Usage
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Here are some examples of using this model in MLC LLM.
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Before running the examples, please install MLC LLM by following the [installation documentation](https://llm.mlc.ai/docs/install/mlc_llm.html#install-mlc-packages).
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### Chat
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In command line, run
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```bash
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mlc_llm chat HF://mlc-ai/Llama-3-8B-Instruct-q0f32-MLC
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```
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### REST Server
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In command line, run
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```bash
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mlc_llm serve HF://mlc-ai/Llama-3-8B-Instruct-q0f32-MLC
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```
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### Python API
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```python
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from mlc_llm import MLCEngine
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# Create engine
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model = "HF://mlc-ai/Llama-3-8B-Instruct-q0f32-MLC"
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engine = MLCEngine(model)
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# Run chat completion in OpenAI API.
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for response in engine.chat.completions.create(
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messages=[{"role": "user", "content": "What is the meaning of life?"}],
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model=model,
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stream=True,
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):
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for choice in response.choices:
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print(choice.delta.content, end="", flush=True)
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print("\n")
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engine.terminate()
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```
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## Documentation
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For more information on MLC LLM project, please visit our [documentation](https://llm.mlc.ai/docs/) and [GitHub repo](http://github.com/mlc-ai/mlc-llm).
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