Image-to-Text
Transformers
ONNX
Safetensors
vision-encoder-decoder
image-text-to-text
trocr
ocr
captcha
math-captcha
synthetic-data
Instructions to use arkhabbazan/ocr-math-captcha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arkhabbazan/ocr-math-captcha 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="arkhabbazan/ocr-math-captcha")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("arkhabbazan/ocr-math-captcha") model = AutoModelForMultimodalLM.from_pretrained("arkhabbazan/ocr-math-captcha", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c49b80baf097255998cc57476744214b0d6711d064dc94c60354c8dd992ad00d
- Size of remote file:
- 88 MB
- SHA256:
- a0f56392c2eefbf7116a98bf95bcbc3d33457fc5ffd999733c93cca02de978e0
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