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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: dphn/Dolphin3.0-R1-Mistral-24B
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+ pipeline_tag: text-generation
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+ library_name: transformers
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+ tags:
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+ - mlx
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+ ---
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+
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+ # introvoyz041/Dolphin3.0-R1-Mistral-24B-mlx-4Bit
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+
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+ The Model [introvoyz041/Dolphin3.0-R1-Mistral-24B-mlx-4Bit](https://huggingface.co/introvoyz041/Dolphin3.0-R1-Mistral-24B-mlx-4Bit) was converted to MLX format from [dphn/Dolphin3.0-R1-Mistral-24B](https://huggingface.co/dphn/Dolphin3.0-R1-Mistral-24B) using mlx-lm version **0.28.3**.
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("introvoyz041/Dolphin3.0-R1-Mistral-24B-mlx-4Bit")
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+
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+ prompt="hello"
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+
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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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+
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+ response = generate(model, tokenizer, prompt=prompt, verbose=True)
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+ ```