How to use from the
Use from the
MLX library
# 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("mlx-community/phi-1_5")

prompt = "Once upon a time in"
text = generate(model, tokenizer, prompt=prompt, verbose=True)

mlx-community/phi-1_5

The Model mlx-community/phi-1_5 was converted to MLX format from microsoft/phi-1_5 using mlx-lm version 0.16.1.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/phi-1_5")
response = generate(model, tokenizer, prompt="hello", verbose=True)
Downloads last month
40
Safetensors
Model size
1B params
Tensor type
F16
ยท
MLX
Hardware compatibility
Log In to add your hardware

Quantized

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support