Update README.md

README.md

@@ -6,17 +6,140 @@ tags:
 - transformers
 - unsloth
 - gemma3n
+- medical
+- vision-language
+- gemma
+- ecg
+- cardiology
+- healthcare
 license: cc-by-4.0
+datasets:
+  - yasserrmd/pulse-ecg-instruct-subset
 language:
 - en
 ---
 
-# Uploaded finetuned  model
 
-- **Developed by:** yasserrmd
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/gemma-3n-e2b-it-unsloth-bnb-4bit
 
-This gemma3n model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+# yasserrmd/GemmaECG-Vision
+
+`GemmaECG-Vision` is a fine-tuned vision-language model built on `google/gemma-3n-e2b`, designed for ECG image interpretation tasks. The model accepts a medical ECG image along with a clinical instruction prompt and generates a structured analysis suitable for triage or documentation use cases.
+
+This model was developed using **Unsloth** for efficient fine-tuning and supports **image + text** inputs with medical task-specific prompt formatting. It is designed to run in **offline or edge environments**, enabling healthcare triage in resource-constrained settings.
+
+## Model Objective
+
+To assist healthcare professionals and emergency responders by providing AI-generated ECG analysis directly from medical images, without requiring internet access or cloud resources.
+
+## Usage
+
+This model expects:
+- An ECG image (`PIL.Image`)
+- A textual instruction such as:
+
+```
+
+You are a clinical assistant specialized in ECG interpretation. Given an ECG image, generate a concise, structured, and medically accurate report.
+
+Use this exact format:
+
+Rhythm:
+PR Interval:
+QRS Duration:
+Axis:
+Bundle Branch Blocks:
+Atrial Abnormalities:
+Ventricular Hypertrophy:
+Q Wave or QS Complexes:
+T Wave Abnormalities:
+ST Segment Changes:
+Final Impression:
+
+````
+
+### Inference Example (Python)
+
+```python
+from transformers import AutoProcessor, Gemma3nForConditionalGeneration
+from PIL import Image
+import torch
+
+model_id = "yasserrmd/GemmaECG-Vision"
+model = Gemma3nForConditionalGeneration.from_pretrained(model_id, torch_dtype=torch.bfloat16).eval().to("cuda")
+processor = AutoProcessor.from_pretrained(model_id)
+
+image = Image.open("example_ecg.png").convert("RGB")
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image"},
+            {"type": "text", "text": "Interpret this ECG and provide a structured triage report."}
+        ]
+    }
+]
+
+prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
+
+inputs = processor(image, prompt, return_tensors="pt").to("cuda")
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=256,
+    temperature=1.0,
+    top_p=0.95,
+    top_k=64,
+    use_cache=True
+)
+
+result = processor.decode(outputs[0], skip_special_tokens=True)
+print(result)
+````
+
+## Training Details
+
+* **Framework**: Unsloth + TRL SFTTrainer
+* **Hardware**: Google Colab Pro (L4)
+* **Batch Size**: 2
+* **Epochs**: 1
+* **Learning Rate**: 2e-4
+* **Scheduler**: Cosine
+* **Loss**: CrossEntropy
+* **Precision**: bfloat16
+
+## Dataset
+
+The training dataset is a curated subset of the [PULSE-ECG/ECGInstruct](https://huggingface.co/datasets/PULSE-ECG/ECGInstruct) dataset, reformatted for VLM instruction tuning.
+
+* 3,272 samples of ECG image + structured instruction + clinical output
+* Focused on realistic and medically relevant triage cases
+
+Dataset link: [`yasserrmd/pulse-ecg-instruct-subset`](https://huggingface.co/datasets/yasserrmd/pulse-ecg-instruct-subset)
+
+## Intended Use
+
+* Emergency triage in offline settings
+* On-device ECG assessment
+* Integration with medical edge devices (Jetson, Pi, Android)
+* Rapid analysis during disaster response
+
+## Limitations
+
+* Not intended to replace licensed medical professionals
+* Accuracy may vary depending on image quality
+* Model outputs should be reviewed by a clinician before action
+
+## License
+
+This model is licensed under **CC BY 4.0**. You are free to use, modify, and distribute it with attribution.
+
+## Author
+
+Mohamed Yasser
+[Hugging Face Profile](https://huggingface.co/yasserrmd)
+
+
+
 
 [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)