Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+tags:
+- ocr
+- handwritten-text
+- trocr
+- pytorch
+---
+
+# Model Name: TrOCR Fine-Tuned on Custom Dataset
+
+This model is a fine-tuned version of Microsoft's `TrOCR` on a custom dataset for handwritten text extraction from scanned documents.
+
+## 🧠 Model Architecture
+- **Base model**: Microsoft TrOCR (base)
+- **Used with**: CRAFT for text detection
+- **Fine-tuned with**: OCR-specific dataset
+
+## 📁 Files in this repository:
+- `pytorch_model.bin`: Model weights (2.1 GB)
+- `config.json`, `tokenizer_config.json`, etc.
+- Training and evaluation scripts (optional)
+
+## 🚀 How to Use
+
+```python
+from transformers import VisionEncoderDecoderModel, TrOCRProcessor
+from PIL import Image
+import torch
+
+# Load processor and model
+processor = TrOCRProcessor.from_pretrained("Gitesh2003/MESA_TrOCR")
+model = VisionEncoderDecoderModel.from_pretrained("Gitesh2003/MESA_TrOCR")
+
+# Load image
+image = Image.open("sample_image.jpg").convert("RGB")
+
+# OCR
+pixel_values = processor(images=image, return_tensors="pt").pixel_values
+generated_ids = model.generate(pixel_values)
+generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+
+print(generated_text)