mlabonne/FineTome-100k
Viewer • Updated • 100k • 20.7k • 269
How to use Felprot75/dolphin-2.9.4-llama3.1-8b-Q8-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir dolphin-2.9.4-llama3.1-8b-Q8-mlx Felprot75/dolphin-2.9.4-llama3.1-8b-Q8-mlx
The Model Felprot75/dolphin-2.9.4-llama3.1-8b-Q8-mlx was converted to MLX format from cognitivecomputations/dolphin-2.9.4-llama3.1-8b using mlx-lm version 0.19.1.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Felprot75/dolphin-2.9.4-llama3.1-8b-Q8-mlx")
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)
8-bit
Base model
meta-llama/Llama-3.1-8B