27ab3abd12
Model: usermma/Granite-4.1-30B-Claude-4.6-Opus-Thinking-Charles-Xavier-mlx-fp16 Source: Original Platform
41 lines
1.2 KiB
Markdown
41 lines
1.2 KiB
Markdown
---
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license: apache-2.0
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base_model: DavidAU/Granite-4.1-30B-Claude-4.6-Opus-Thinking-Charles-Xavier
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- finetune
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- unsloth
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- granite-4.1
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- reasoning
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- thinking
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- mlx
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- mlx-my-repo
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---
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# usermma/Granite-4.1-30B-Claude-4.6-Opus-Thinking-Charles-Xavier-mlx-fp16
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The Model [usermma/Granite-4.1-30B-Claude-4.6-Opus-Thinking-Charles-Xavier-mlx-fp16](https://huggingface.co/usermma/Granite-4.1-30B-Claude-4.6-Opus-Thinking-Charles-Xavier-mlx-fp16) was converted to MLX format from [DavidAU/Granite-4.1-30B-Claude-4.6-Opus-Thinking-Charles-Xavier](https://huggingface.co/DavidAU/Granite-4.1-30B-Claude-4.6-Opus-Thinking-Charles-Xavier) using mlx-lm version **0.31.2**.
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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("usermma/Granite-4.1-30B-Claude-4.6-Opus-Thinking-Charles-Xavier-mlx-fp16")
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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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