Instructions to use madroid/phi2-4bit-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use madroid/phi2-4bit-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("madroid/phi2-4bit-mlx") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use madroid/phi2-4bit-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "madroid/phi2-4bit-mlx" --prompt "Once upon a time"
metadata
language:
- en
license: mit
tags:
- nlp
- code
- mlx
license_link: https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE
pipeline_tag: text-generation
madroid/phi2-4bit-mlx
This model was converted to MLX format from microsoft/phi-2.
Refer to the original model card for more details on the model.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("madroid/phi2-4bit-mlx")
response = generate(model, tokenizer, prompt="hello", verbose=True)