metadata
license: mit
license_link: >-
https://huggingface.co/microsoft/Phi-3-medium-128k-instruct/resolve/main/LICENSE
language:
- multilingual
pipeline_tag: text-generation
tags:
- nlp
- code
- mlx
- mlx-my-repo
inference:
parameters:
temperature: 0.7
widget:
- messages:
- role: user
content: Can you provide ways to eat combinations of bananas and dragonfruits?
base_model: microsoft/Phi-3-medium-128k-instruct
tslim1/Phi-3-medium-128k-instruct-mlx-8Bit
The Model tslim1/Phi-3-medium-128k-instruct-mlx-8Bit was converted to MLX format from microsoft/Phi-3-medium-128k-instruct using mlx-lm version 0.26.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("tslim1/Phi-3-medium-128k-instruct-mlx-8Bit")
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)