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--- |
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library_name: mlc-llm |
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base_model: HuggingFaceTB/SmolLM2-135M-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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# SmolLM2-135M-Instruct-q0f16-MLC |
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This is the [SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) model in MLC format `q0f16`. |
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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/SmolLM2-135M-Instruct-q0f16-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/SmolLM2-135M-Instruct-q0f16-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/SmolLM2-135M-Instruct-q0f16-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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