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--- |
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base_model: Ransaka/sinhala-ocr-model |
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model-index: |
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- name: sinhala-ocr-model-v2 |
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results: [] |
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pipeline_tag: image-to-text |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# TrOCR-Sinhala |
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See training metrics tab for performance details. |
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## Model description |
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This model is finetuned version of Microsoft [TrOCR Printed](https://huggingface.co/microsoft/trocr-base-printed) |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Example |
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```python |
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from PIL import Image |
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import requests |
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from io import BytesIO |
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from transformers import TrOCRProcessor, VisionEncoderDecoderModel, AutoTokenizer |
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image_url = "https://datasets-server.huggingface.co/assets/Ransaka/sinhala_synthetic_ocr/--/bf7c8a455b564cd73fe035031e19a5f39babb73b/--/default/train/0/image/image.jpg" |
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response = requests.get(image_url) |
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img = Image.open(BytesIO(response.content)) |
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processor = TrOCRProcessor.from_pretrained('Ransaka/TrOCR-Sinhala') |
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model = VisionEncoderDecoderModel.from_pretrained('Ransaka/TrOCR-Sinhala') |
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model.to("cuda:0") |
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pixel_values = processor(img, return_tensors="pt").pixel_values.to('cuda:0') |
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generated_ids = model.generate(pixel_values,num_beams=2,early_stopping=True) |
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generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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generated_text #දිවයිනට බලයට ඇති ආපදා තත්ත්වය හමුවේ සබරගමුව පළාතේ |
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``` |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
