Image-to-Text
Transformers
PyTorch
Korean
vision-encoder-decoder
image-text-to-text
donut
document-understanding
ocr-free
korean
Instructions to use ksk00/donut-docai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ksk00/donut-docai 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="ksk00/donut-docai", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("ksk00/donut-docai") model = AutoModelForMultimodalLM.from_pretrained("ksk00/donut-docai", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16cebb37c03dadc5bda5da588ae74e45a847e0760557c9f35cdbb751ddebad3e
- Size of remote file:
- 809 MB
- SHA256:
- 1c42979ff5e88e2a28f952162e8a2a9762c9bfe997bb71ab9384ff97d893ec23
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