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