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---
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2024-12-19 18:25:40 +08:00
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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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- mlx
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base_model: NousResearch/Hermes-3-Llama-3.2-3B
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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: Write a short story about Goku discovering kirby has teamed up with Majin
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Buu to destroy the world.
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library_name: transformers
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model-index:
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- name: Hermes-3-Llama-3.1-405B
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results: []
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---
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2024-12-19 10:21:28 +00:00
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2024-12-19 18:25:40 +08:00
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# mlx-community/Hermes-3-Llama-3.2-3B-bf16
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2024-12-19 18:25:40 +08:00
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The Model [mlx-community/Hermes-3-Llama-3.2-3B-bf16](https://huggingface.co/mlx-community/Hermes-3-Llama-3.2-3B-bf16) was
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converted to MLX format from [NousResearch/Hermes-3-Llama-3.2-3B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.2-3B)
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using mlx-lm version **0.20.3**.
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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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2024-12-19 18:25:40 +08:00
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2024-12-19 10:21:28 +00:00
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("mlx-community/Hermes-3-Llama-3.2-3B-bf16")
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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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