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Model: lgsantini1/qwen3-8b-medical
Source: Original Platform

README.md

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+---
+base_model: unsloth/Qwen3-8B-unsloth-bnb-4bit
+tags:
+- text-generation
+- conversational
+- medical
+- qa
+- transformers
+- unsloth
+- qwen3
+license: apache-2.0
+language:
+- 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)
+```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))