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--- |
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license: apache-2.0 |
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tags: |
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- mlx |
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base_model: FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-Flash-32B-Preview |
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--- |
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# bobig/FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8 |
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Quant made with the latest mlx-lm |
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This model is very good, my 2nd favorite for unpluged coding on Macs. |
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SpecDec works with this draft model [DeepScaleR-1.5B-Preview-Q8](https://huggingface.co/mlx-community/DeepScaleR-1.5B-Preview-Q8) |
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but the acceptance rate is only 61%. |
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The Model [bobig/FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8](https://huggingface.co/bobig/FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8) was |
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converted to MLX format from [FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-Flash-32B-Preview](https://huggingface.co/FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-Flash-32B-Preview) |
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using mlx-lm version **0.21.4**. |
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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("bobig/FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8") |
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prompt = "hello" |
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if 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, 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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