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--- |
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datasets: |
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- cognitivecomputations/dolphin-r1 |
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- OpenCoder-LLM/opc-sft-stage1 |
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- OpenCoder-LLM/opc-sft-stage2 |
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- microsoft/orca-agentinstruct-1M-v1 |
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- microsoft/orca-math-word-problems-200k |
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- NousResearch/hermes-function-calling-v1 |
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- AI-MO/NuminaMath-CoT |
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- AI-MO/NuminaMath-TIR |
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- allenai/tulu-3-sft-mixture |
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- cognitivecomputations/dolphin-coder |
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- HuggingFaceTB/smoltalk |
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- cognitivecomputations/samantha-data |
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- m-a-p/CodeFeedback-Filtered-Instruction |
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- m-a-p/Code-Feedback |
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language: |
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- en |
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base_model: cognitivecomputations/Dolphin3.0-R1-Mistral-24B |
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tags: |
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- mlx |
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--- |
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# maxrubin629/Dolphin3.0-R1-Mistral-24B-Q4-mlx |
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The Model [maxrubin629/Dolphin3.0-R1-Mistral-24B-Q4-mlx](https://huggingface.co/maxrubin629/Dolphin3.0-R1-Mistral-24B-Q4-mlx) was converted to MLX format from [cognitivecomputations/Dolphin3.0-R1-Mistral-24B](https://huggingface.co/cognitivecomputations/Dolphin3.0-R1-Mistral-24B) using mlx-lm version **0.20.5**. |
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## Use with mlx |
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```bash |
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pip install mlx-lm |
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``` |
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```python |
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from mlx_lm import load, generate |
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model, tokenizer = load("maxrubin629/Dolphin3.0-R1-Mistral-24B-Q4-mlx") |
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prompt="hello" |
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if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: |
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messages = [{"role": "user", "content": prompt}] |
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prompt = tokenizer.apply_chat_template( |
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messages, tokenize=False, add_generation_prompt=True |
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) |
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response = generate(model, tokenizer, prompt=prompt, verbose=True) |
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``` |
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