mlx-quants
Collection
I have never used Apple products • 17 items • Updated
# Install MLX LM
uv tool install mlx-lm# Start the server
mlx_lm.server --model "MuXodious/Rocinante-XL-16B-v1-absolute-heresy-mlx-MXFP8"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "MuXodious/Rocinante-XL-16B-v1-absolute-heresy-mlx-MXFP8",
"messages": [
{"role": "user", "content": "Hello"}
]
}'This model MuXodious/Rocinante-XL-16B-v1-absolute-heresy-mlx-MXFP8 was converted to MLX format from MuXodious/Rocinante-XL-16B-v1-absolute-heresy using mlx-lm version 0.31.1.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("MuXodious/Rocinante-XL-16B-v1-absolute-heresy-mlx-MXFP8")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
8-bit
Base model
TheDrummer/Rocinante-XL-16B-v1
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm# Interactive chat REPL mlx_lm.chat --model "MuXodious/Rocinante-XL-16B-v1-absolute-heresy-mlx-MXFP8"