mlx-quants
Collection
I have never used Apple products • 17 items • Updated
# Install Pi:
npm install -g @mariozechner/pi-coding-agent# Add to ~/.pi/agent/models.json:
{
"providers": {
"mlx-lm": {
"baseUrl": "http://localhost:8080/v1",
"api": "openai-completions",
"apiKey": "none",
"models": [
{
"id": "MuXodious/Rocinante-XL-16B-v1-absolute-heresy-mlx-MXFP8"
}
]
}
}
}# Start Pi in your project directory:
piThis 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
Start the MLX server
# Install MLX LM: uv tool install mlx-lm# Start a local OpenAI-compatible server: mlx_lm.server --model "MuXodious/Rocinante-XL-16B-v1-absolute-heresy-mlx-MXFP8"