metadata
license: mit
datasets:
- microsoft/mediflow
- ncbi/pubmed
- epfl-llm/guidelines
- starmpcc/Asclepius-Synthetic-Clinical-Notes
- akemiH/NoteChat
- zhengyun21/PMC-Patients
- jpcorb20/medical_wikipedia
language:
- en
base_model: microsoft/MediPhi-Instruct
library_name: mlx
tags:
- merge
- mergekit
- medical
- clinical
- mlx
pipeline_tag: text-generation
mlx-community/MediPhi-Instruct-bf16
This model mlx-community/MediPhi-Instruct-bf16 was converted to MLX format from microsoft/MediPhi-Instruct using mlx-lm version 0.25.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/MediPhi-Instruct-bf16")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)