mlc-ai/Mistral-7B-Instruct-v0.2-q3f16_1-MLC
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spydaz
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- README.md +0 -57
- mlc-chat-config.json +2 -35
- tensor-cache.json +0 -0
README.md
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---
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library_name: mlc-llm
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base_model: mistralai/Mistral-7B-Instruct-v0.2
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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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# Mistral-7B-Instruct-v0.2-q3f16_1-MLC
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This is the [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) model in MLC format `q3f16_1`.
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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/Mistral-7B-Instruct-v0.2-q3f16_1-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/Mistral-7B-Instruct-v0.2-q3f16_1-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/Mistral-7B-Instruct-v0.2-q3f16_1-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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mlc-chat-config.json
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"sliding_window_size": 1024,
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"prefill_chunk_size": 128,
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"attention_sink_size": 4,
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"tensor_parallel_shards": 1
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"max_batch_size": 80
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},
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"vocab_size": 32000,
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"context_window_size": -1,
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"temperature": 0.7,
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"repetition_penalty": 1.0,
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"top_p": 0.95,
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"conv_template":
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"name": "mistral_default",
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"system_template": "[INST] {system_message}",
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"system_message": "Always assist with care, respect, and truth. Respond with utmost utility yet securely. Avoid harmful, unethical, prejudiced, or negative content. Ensure replies promote fairness and positivity.",
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"system_prefix_token_ids": [
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1
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],
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"add_role_after_system_message": false,
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"roles": {
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"user": "[INST]",
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"assistant": "[/INST]",
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"tool": "[INST]"
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},
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"role_templates": {
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"user": "{user_message}",
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"assistant": "{assistant_message}",
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"tool": "{tool_message}"
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},
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"messages": [],
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"seps": [
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" "
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],
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"role_content_sep": " ",
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"role_empty_sep": "",
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"stop_str": [
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"</s>"
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],
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"stop_token_ids": [
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2
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],
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"function_string": "",
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"use_function_calling": false
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},
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"pad_token_id": 0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"sliding_window_size": 1024,
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"prefill_chunk_size": 128,
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"attention_sink_size": 4,
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"tensor_parallel_shards": 1
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},
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"vocab_size": 32000,
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"context_window_size": -1,
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"temperature": 0.7,
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"repetition_penalty": 1.0,
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"top_p": 0.95,
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"conv_template": "mistral_default",
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"pad_token_id": 0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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tensor-cache.json
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