Instructions to use naver-clova-ix/donut-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naver-clova-ix/donut-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="naver-clova-ix/donut-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("naver-clova-ix/donut-base") model = AutoModelForMultimodalLM.from_pretrained("naver-clova-ix/donut-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from naver-clova-ix/donut-base: direct link, hf CLI and curl.
- Browser
- Download file 809 MB
-
https://huggingface.co/naver-clova-ix/donut-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://naver-clova-ix/donut-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/naver-clova-ix/donut-base/resolve/main/pytorch_model.bin
809 MB
- Xet hash:
- 7eb3d1ffb52f44f2d45c5b8fc18bd0fc026c5a48a944757cb958ac11110f74cc
- Size of remote file:
- 809 MB
- SHA256:
- 749f6e487d0cdbd7362d8b6a909174b93506d8631da0d15a6108bb6512ad5f48
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