Update README.md

README.md

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----
-license: mit
----
+---
+tags:
+- trocr
+- ocr
+- text-recognition
+- pytorch
+- fine-tuned
+license: mit
+---
+
+# 🏆 TrOCR Fine-Tuned Model (Handwritten Text Recognition)
+
+## 📌 **Model Overview**
+This is a fine-tuned **Microsoft TrOCR Large** model for **handwritten text recognition**. It has been trained on a dataset containing scanned handwritten documents.
+
+- **Base Model:** Microsoft TrOCR Large
+- **Fine-tuned On:** IAM Handwritten Dataset
+- **Use Case:** Extract text from scanned handwritten documents
+- **Framework:** PyTorch + Transformers (Hugging Face)
+- **Large File Support:** Uses `git-lfs` for model files
+
+---
+
+## 🚀 **How to Use This Model**
+You can load and use the fine-tuned model with `transformers` in Python as follows:
+
+```python
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+from PIL import Image
+
+# Load model and processor
+processor = TrOCRProcessor.from_pretrained("Gitesh2003/TrOCR")
+model = VisionEncoderDecoderModel.from_pretrained("Gitesh2003/TrOCR")
+
+# Load an image
+image = Image.open("handwritten_sample.jpg").convert("RGB")
+
+# Process and predict text
+pixel_values = processor(images=image, return_tensors="pt").pixel_values
+generated_ids = model.generate(pixel_values)
+extracted_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+
+print("Extracted Text:", extracted_text)