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)