base_model, tags, license, language

base_model	tags	license	language
unsloth/Qwen3-8B-unsloth-bnb-4bit	text-generation conversational medical qa transformers unsloth qwen3	apache-2.0	en pt

Qwen3-8B Medical (Fine-tuned)

• Developed by: lgsantini1
• License: apache-2.0
• Finetuned from: unsloth/Qwen3-8B-unsloth-bnb-4bit

Overview

This is a Qwen3-8B model fine-tuned for medical-style question answering based on publicly available QA datasets.

Training data

This model was fine-tuned using data sourced from:

• PubMedQA — A dataset of question answering pairs grounded in biomedical research abstracts.
  Repo: https://github.com/pubmedqa/pubmedqa
  (Used only the content available in the repository; no additional web crawling.)

If you also used other datasets (e.g., MedQuAD), add them here with links and licenses.

Intended use

• Educational / informational assistance for medical QA style prompts.
• Useful for summarization, explanation of concepts, and drafting answers that should be verified.

Limitations & safety

• This model can hallucinate or provide incomplete/incorrect medical guidance.
• Not a medical device. Do not use for diagnosis, treatment decisions, or emergency situations.
• Always verify answers with reliable sources and qualified professionals.

How to use

Transformers (Python)

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

repo_id = "lgsantini1/qwen3-8b-medical"

tok = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype="auto", device_map="auto")

prompt = "Explain hypertension in simple terms."
inputs = tok(prompt, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=200)
print(tok.decode(out[0], skip_special_tokens=True))