Text Generation
MLX
Safetensors
English
llama
Llama-3
instruct
finetune
chatml
gpt4
synthetic data
distillation
function calling
json mode
axolotl
roleplaying
chat
conversational
Instructions to use mlx-community/Hermes-3-Llama-3.1-8B-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Hermes-3-Llama-3.1-8B-MLX with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/Hermes-3-Llama-3.1-8B-MLX") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mlx-community/Hermes-3-Llama-3.1-8B-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mlx-community/Hermes-3-Llama-3.1-8B-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/Hermes-3-Llama-3.1-8B-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlx-community/Hermes-3-Llama-3.1-8B-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
mlx-community/Hermes-3-Llama-3.1-8B-MLX
This model mlx-community/Hermes-3-Llama-3.1-8B-MLX was converted to MLX format from NousResearch/Hermes-3-Llama-3.1-8B using mlx-lm version 0.23.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Hermes-3-Llama-3.1-8B-MLX")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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Model size
8B params
Tensor type
F16
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Hardware compatibility
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Model tree for mlx-community/Hermes-3-Llama-3.1-8B-MLX
Base model
meta-llama/Llama-3.1-8B Finetuned
NousResearch/Hermes-3-Llama-3.1-8B