Image-to-Text
Transformers
PyTorch
TensorBoard
English
vision-encoder-decoder
image-text-to-text
Generated from Trainer
Instructions to use DunnBC22/trocr-base-printed_captcha_ocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/trocr-base-printed_captcha_ocr 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="DunnBC22/trocr-base-printed_captcha_ocr")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("DunnBC22/trocr-base-printed_captcha_ocr") model = AutoModelForImageTextToText.from_pretrained("DunnBC22/trocr-base-printed_captcha_ocr") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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README.md
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tags:
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model-index:
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- name: trocr-base-printed_captcha_ocr
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results: []
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language:
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metrics:
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pipeline_tag: image-to-text
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# trocr-base-printed_captcha_ocr
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language:
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tags:
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- generated_from_trainer
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metrics:
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pipeline_tag: image-to-text
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base_model: microsoft/trocr-base-printed
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model-index:
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- name: trocr-base-printed_captcha_ocr
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results: []
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# trocr-base-printed_captcha_ocr
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