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README.md
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---
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language:
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- en
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license: llama3
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tags:
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- Llama-3
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- instruct
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- finetune
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- chatml
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- gpt4
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- synthetic data
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- distillation
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- function calling
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- json mode
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- axolotl
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- roleplaying
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- chat
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- reasoning
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- r1
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- vllm
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- mlx
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- mlx-my-repo
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base_model: NousResearch/DeepHermes-3-Llama-3-3B-Preview
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widget:
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- example_title: Hermes 3
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messages:
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- role: system
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content: You are a sentient, superintelligent artificial general intelligence,
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here to teach and assist me.
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- role: user
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content: What is the meaning of life?
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library_name: transformers
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model-index:
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- name: DeepHermes-3-Llama-3.1-3B
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results: []
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---
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# ncls-p/DeepHermes-3-Llama-3-3B-Preview-mlx-4Bit
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The Model [ncls-p/DeepHermes-3-Llama-3-3B-Preview-mlx-4Bit](https://huggingface.co/ncls-p/DeepHermes-3-Llama-3-3B-Preview-mlx-4Bit) was converted to MLX format from [NousResearch/DeepHermes-3-Llama-3-3B-Preview](https://huggingface.co/NousResearch/DeepHermes-3-Llama-3-3B-Preview) using mlx-lm version **0.21.5**.
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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("ncls-p/DeepHermes-3-Llama-3-3B-Preview-mlx-4Bit")
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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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