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:
- d53bb8d545a9b33325e44f1d02bd3cea4fc8c14d048c6047beb8c91353b5d63e
- Size of remote file:
- 1.2 GB
- SHA256:
- 7e9865d42b16b60fbac4a5c3510951c8aa9c32b60c3a70099b2c8878543920f0
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