Instructions to use Graf-J/captcha-crnn-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Graf-J/captcha-crnn-base 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="Graf-J/captcha-crnn-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Graf-J/captcha-crnn-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add Live-Demo to Readme
Browse files
README.md
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# ✨ DeepCaptcha-CRNN: Sequential Vision for OCR
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### CRNN Base
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[](https://opensource.org/licenses/MIT)
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[](https://www.python.org/downloads/release/python-3130/)
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[](https://huggingface.co/Graf-J/captcha-crnn-finetuned)
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---
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<img src="images/CAPTCHA.png" alt="Captcha Example" width="500">
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# ✨ DeepCaptcha-CRNN: Sequential Vision for OCR
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### CRNN Base
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[](https://opensource.org/licenses/MIT)
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[](https://www.python.org/downloads/release/python-3130/)
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[](https://huggingface.co/Graf-J/captcha-crnn-finetuned)
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🚀 **Live Demo:**
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👉 [Try the Model in Your Browser](https://huggingface.co/spaces/Graf-J/Captcha-Demo)
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---
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<img src="images/CAPTCHA.png" alt="Captcha Example" width="500">
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