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--- |
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language: |
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- zh |
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- en |
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- fr |
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- de |
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- ja |
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- ko |
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- it |
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- fi |
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tags: |
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- qwen3 |
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- mlx |
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- mlx-my-repo |
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pipeline_tag: text-generation |
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base_model: OpenBuddy/SimpleChat-30BA3B-V2 |
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--- |
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# mrtoots/SimpleChat-30BA3B-V2-mlx-8Bit |
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The Model [mrtoots/SimpleChat-30BA3B-V2-mlx-8Bit](https://huggingface.co/mrtoots/SimpleChat-30BA3B-V2-mlx-8Bit) was converted to MLX format from [OpenBuddy/SimpleChat-30BA3B-V2](https://huggingface.co/OpenBuddy/SimpleChat-30BA3B-V2) using mlx-lm version **0.26.4**. |
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## Toots' Note: |
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This model was converted and quantized utilizing OpenBuddy's base version of SimpleChat-30BA3B-V2. |
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Please follow and support [OpenBuddy's work](https://huggingface.co/OpenBuddy) if you like it! |
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🦛 <span style="color:#800080">If you want a free consulting session, </span>[fill out this form](https://forms.gle/xM9gw1urhypC4bWS6) <span style="color:#800080">to get in touch!</span> 🤗 |
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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("mrtoots/SimpleChat-30BA3B-V2-mlx-8Bit") |
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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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