Instructions to use intexcp/donut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intexcp/donut 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="intexcp/donut")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("intexcp/donut", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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The Donut (end-to-end transformer) model for text recognition
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```
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from transformers import AutoTokenizer, AutoModelForImageTextToText, AutoProcessor
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from datasets import load_dataset
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The Donut (end-to-end transformer) model for text recognition
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Using:
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```
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from transformers import AutoTokenizer, AutoModelForImageTextToText, AutoProcessor
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from datasets import load_dataset
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