Image-to-Text
Transformers
TensorBoard
Safetensors
Sinhala
vision-encoder-decoder
image-text-to-text
Instructions to use Ransaka/TrOCR-Sinhala with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ransaka/TrOCR-Sinhala with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="Ransaka/TrOCR-Sinhala")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Ransaka/TrOCR-Sinhala") model = AutoModelForMultimodalLM.from_pretrained("Ransaka/TrOCR-Sinhala") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9991253075f0c4b8a3ccf131669a142587fbb8000c2d8bdc924c9793729677c0
- Size of remote file:
- 4.28 kB
- SHA256:
- 1b9f5fda763ce265147871a250580f76aaca5702d2bfa9b208b67d5e7bf64061
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