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metadata
language:
  - en
license: llama3
tags:
  - Llama-3
  - instruct
  - finetune
  - chatml
  - gpt4
  - synthetic data
  - distillation
  - function calling
  - json mode
  - axolotl
  - roleplaying
  - chat
  - mlx
base_model: NousResearch/Hermes-3-Llama-3.1-8B
widget:
  - example_title: Hermes 3
    messages:
      - role: system
        content: >-
          You are a sentient, superintelligent artificial general intelligence,
          here to teach and assist me.
      - role: user
        content: What is the meaning of life?
model-index:
  - name: Hermes-3-Llama-3.1-70B
    results: []

mlx-community/Hermes-3-Llama-3.1-8B-3bit

The Model mlx-community/Hermes-3-Llama-3.1-8B-3bit was converted to MLX format from NousResearch/Hermes-3-Llama-3.1-8B using mlx-lm version 0.20.4.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Hermes-3-Llama-3.1-8B-3bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)