Update README.md

README.md

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----
-license: apache-2.0
----
+
+---
+license: apache-2.0
+tags:
+  - medical
+  - chest-xray
+  - reasoning
+  - vision-language
+  - medgemma
+---
+
+# 🧠 MedGEMMA Reasoning Model — Fine-tuned on CXR-10K
+
+This is a fine-tuned version of `google/medgemma-4b-it`, trained on the [CXR-10K Reasoning Dataset](https://huggingface.co/datasets/Manusinhh/cxr-10k-reasoning-dataset) consisting of chest X-ray images paired with step-by-step clinical reasoning.
+
+---
+
+## 🩻 Task
+
+**Multimodal Clinical Reasoning**:  
+Given a chest X-ray image, the model generates a step-by-step diagnostic reasoning path covering:
+
+- Lung fields
+- Cardiac size
+- Mediastinal structures
+- Surgical history
+- Skeletal findings
+
+---
+
+## 🧪 Example Usage (Inference)
+
+```python
+from transformers import AutoProcessor, AutoModelForImageTextToText
+from PIL import Image
+import torch
+
+# Load model and processor
+model = AutoModelForImageTextToText.from_pretrained("Manusinhh/medgemma-finetuned-cxr-reasoning")
+processor = AutoProcessor.from_pretrained("google/medgemma-4b-it")
+
+# Load image
+image = Image.open("example.png").convert("RGB")
+
+# Create prompt
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image", "image": image},
+            {"type": "text", "text": "Analyze this medical image and provide step-by-step findings."}
+        ]
+    }
+]
+
+# Tokenize and generate
+inputs = processor.apply_chat_template(messages, tokenize=True, return_tensors="pt").to(model.device)
+with torch.no_grad():
+    output = model.generate(**inputs, max_new_tokens=300)
+
+print(processor.decode(output[0], skip_special_tokens=True))
+````
+
+---
+
+## 📊 Training Details
+
+* **Base model**: `google/medgemma-4b-it`
+* **LoRA Fine-tuning**: Used `peft` with low-rank adapters
+* **Training set**: 10k chest X-ray samples with reasoning steps
+* **Frameworks**: HuggingFace Transformers, TRL, PEFT, DeepSpeed
+
+---
+
+## 📚 Dataset Attribution
+
+Training data derived from:
+[CXR-10K Reasoning Dataset](https://huggingface.co/datasets/Manusinhh/cxr-10k-reasoning-dataset)
+Built upon:
+[itsanmolgupta/mimic-cxr-dataset-10k](https://huggingface.co/datasets/itsanmolgupta/mimic-cxr-dataset-10k)
+
+Base dataset:
+[MIMIC-CXR](https://physionet.org/content/mimic-cxr/2.0.0/) by MIT LCP
+
+> Johnson AE, Pollard TJ, Berkowitz SJ, et al. *Scientific Data*. 2019;6:317. [https://doi.org/10.1038/s41597-019-0322-0](https://doi.org/10.1038/s41597-019-0322-0)
+
+```
+