metadata
license: apache-2.0
language:
- en
- ro
base_model: drwlf/Medra4b
datasets:
- drwlf/medra-thinking-768
tags:
- text-generation
- medical-ai
- summarization
- diagnostic-reasoning
- gemma-3
- fine-tuned
- mlx
model_size: 4B
version: Medra v1 – Gemma Edition
format: GGUF (Q4, Q8, BF16)
author: Dr. Alexandru Lupoi & @nicoboss
pipeline_tag: text-generation
library_name: mlx
Medra4b-q8-mlx
This model Medra4b-q8-mlx was converted to MLX format from drwlf/Medra4b using mlx-lm version 0.26.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Medra4b-q8-mlx")
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)