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 AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("intexcp/donut") model = AutoModelForMultimodalLM.from_pretrained("intexcp/donut", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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library_name: transformers
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# Model Card for Model ID
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library_name: transformers
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license: mit
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language:
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- ru
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base_model:
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- Akajackson/donut_rus
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- naver-clova-ix/donut-base
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pipeline_tag: image-to-text
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# Model Card for Model ID
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