Instructions to use aimeri/Rocinante-12B-v1.1-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use aimeri/Rocinante-12B-v1.1-6bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Rocinante-12B-v1.1-6bit aimeri/Rocinante-12B-v1.1-6bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
metadata
license: other
tags:
- mlx
base_model: TheDrummer/Rocinante-12B-v1.1
aimeri/Rocinante-12B-v1.1-6bit
The Model aimeri/Rocinante-12B-v1.1-6bit was converted to MLX format from TheDrummer/Rocinante-12B-v1.1 using mlx-lm version 0.21.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("aimeri/Rocinante-12B-v1.1-6bit")
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)