first commit

app.py

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+from transformers import ViTFeatureExtractor, BertTokenizer, VisionEncoderDecoderModel, AutoTokenizer
+import gradio as gr
+
+model=VisionEncoderDecoderModel.from_pretrained("priyank-m/vit-bert-OCR")
+tokenizer =  AutoTokenizer.from_pretrained("bert-base-multilingual-cased")
+feature_extractor = ViTFeatureExtractor.from_pretrained("google/vit-large-patch32-384")
+
+def run_ocr(image):
+  pixel_values = feature_extractor(image, return_tensors="pt").pixel_values
+  # autoregressively generate caption (uses greedy decoding by default )
+  generated_ids = model.generate(pixel_values, max_new_tokens=50)
+  generated_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+  return generated_text
+
+
+demo = gr.Interface(fn=run_ocr, inputs="image", outputs="text")
+demo.launch()

requirements.txt

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+transformers
+torch