Instructions to use AnthroposRex/Phi-lthy4-mlx-4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AnthroposRex/Phi-lthy4-mlx-4Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Phi-lthy4-mlx-4Bit AnthroposRex/Phi-lthy4-mlx-4Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
metadata
license: mit
language:
- en
base_model: SicariusSicariiStuff/Phi-lthy4
widget:
- text: Phi-lthy4
output:
url: >-
https://huggingface.co/SicariusSicariiStuff/Phi-lthy4/resolve/main/Images/Phi-Lthy4.png
tags:
- mlx
AnthroposRex/Phi-lthy4-mlx-4Bit
The Model AnthroposRex/Phi-lthy4-mlx-4Bit was converted to MLX format from SicariusSicariiStuff/Phi-lthy4 using mlx-lm version 0.31.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("AnthroposRex/Phi-lthy4-mlx-4Bit")
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)