Update README.md

README.md

@@ -1,3 +1,136 @@
 ---
 license: cc-by-nc-4.0
+language:
+- it
+tags:
+- llama
+- llama-3
+- meta
+- medical-qa
+- italian
+- biomedical
+- question-answering
+- fine-tuning
+- unsloth
+- bnb
+- 4bit
+- imb
+- Cardiologia
+datasets:
+- praiselab-picuslab/IMB
+base_model:
+- unsloth/Llama-3.2-1B-Instruct-unsloth-bnb-4bit
 ---
+
+# 🧠 Llama-3.2-1B-Instruct — IMB Cardiologia Fine-Tuned Model
+
+This model is a fine-tuned version of [`unsloth/Llama-3.2-1B-Instruct-unsloth-bnb-4bit`](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct-unsloth-bnb-4bit), optimized for **Italian medical question answering**, with a specific focus on **Cardiologia**.
+
+The fine-tuning was performed using a **subset of the IMB (Italian Medical Benchmark) dataset**, specifically:
+- Cardiologia category only
+- ~10,000 training samples
+
+The training was performed using the **Unsloth** library with LoRA fine-tuning, and the adapter weights were later merged into the base model to provide a standalone checkpoint.
+
+This model relies on data from the IMB dataset. **If you use this model in research or applications, you must cite the IMB paper (see Citation section below).**
+
+---
+
+## 📚 Training Dataset — IMB (Italian Medical Benchmark)
+
+IMB is an Italian benchmark for medical question answering, designed to evaluate and improve LLM performance in clinical-domain Italian language understanding and reasoning.
+
+The full dataset includes:
+
+- **IMB-QA**: 782,644 doctor-patient conversations collected from Italian online medical forums
+- **IMB-MCQA**: 25,862 multiple-choice questions derived from Italian medical specialization exams
+
+⚠️ **Important:**
+This model was trained **only on the Cardiologia subset (~10,000 samples)** of IMB, not on the full dataset.
+
+Dataset repository:
+👉 https://github.com/PRAISELab-PicusLab/IMB
+
+---
+
+## 🧪 Usage Example
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("praiselab-picuslab/Llama-3.2-1B-Instruct-Cardiologia")
+tokenizer = AutoTokenizer.from_pretrained("praiselab-picuslab/Llama-3.2-1B-Instruct-Cardiologia")
+
+prompt = "[Example question in Italian about Cardiologia]"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=150)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+---
+
+## ⚠️ Usage Restrictions
+
+* Allowed use: **Non-commercial research only**
+* Redistribution: Not allowed without explicit authorization
+* Mandatory citation: The IMB dataset paper must be cited in any publication or derived work
+
+---
+
+## 📄 Citation
+
+If you use this model, the IMB dataset, or derived outputs in research, please cite:
+
+```bibtex
+@inproceedings{DBLP:conf/clic-it/RomanoRBPM25,
+  author       = {Antonio Romano and
+                  Giuseppe Riccio and
+                  Mariano Barone and
+                  Marco Postiglione and
+                  Vincenzo Moscato},
+  editor       = {Cristina Bosco and
+                  Elisabetta Jezek and
+                  Marco Polignano and
+                  Manuela Sanguinetti},
+  title        = {{IMB:} An Italian Medical Benchmark for Question Answering},
+  booktitle    = {Proceedings of the Eleventh Italian Conference on Computational Linguistics
+                  (CLiC-it 2025), Cagliari, Italy, September 24-26, 2025},
+  series       = {{CEUR} Workshop Proceedings},
+  volume       = {4112},
+  publisher    = {CEUR-WS.org},
+  year         = {2025},
+  url          = {https://ceur-ws.org/Vol-4112/92_main_long.pdf}
+}
+```
+
+---
+
+## 🏗 Training Details
+
+* Base model: `unsloth/Llama-3.2-1B-Instruct-unsloth-bnb-4bit`
+* Fine-tuning method: LoRA (Unsloth)
+* Quantization: 4-bit (BitsAndBytes)
+* Adapter merging: Yes (Full merged model)
+* Language: Italian
+* Domain: Medical — Cardiologia
+* Training size: ~10,000 samples
+
+---
+
+## 📜 License
+
+This work is licensed under a
+[Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License][cc-by-nc-nd].
+
+[![CC BY-NC-ND 4.0][cc-by-nc-nd-image]][cc-by-nc-nd]
+
+[cc-by-nc-nd]: http://creativecommons.org/licenses/by-nc-nd/4.0/
+[cc-by-nc-nd-image]: https://licensebuttons.net/l/by-nc-nd/4.0/88x31.png
+[cc-by-nc-nd-shield]: https://img.shields.io/badge/License-CC%20BY--NC--ND%204.0-lightgrey.svg
+
+---
+
+## 🤝 Acknowledgements
+
+👨‍💻 This project was developed by Mariano Barone, Roberta Di Marino, Francesco Di Serio, Giovanni Dioguardi, Marco Postiglione, Antonio Romano, Giuseppe Riccio, and Vincenzo Moscato at University of Naples, Federico II