license: apache-2.0 language:

• en
• ro datasets:
• nicoboss/medra-medical tags:
• medical-ai
• clinical-reasoning
• summarization
• diagnosis
• medgemma
• fine-tuned
• mlx
• mlx-my-repo version: DrMedra v1 – MedGemma Edition author: Dr. Alexandru Lupoi & @nicoboss base_model: drwlf/DrMedra4B-abliterated pipeline_tag: text-generation

jc2375/DrMedra4B-abliterated-mlx-fp16

The Model jc2375/DrMedra4B-abliterated-mlx-fp16 was converted to MLX format from drwlf/DrMedra4B-abliterated using mlx-lm version 0.26.4.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("jc2375/DrMedra4B-abliterated-mlx-fp16")

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)