Image-to-Text
Transformers
PyTorch
vision-encoder-decoder
image-text-to-text
donut
vision
endpoints-template
Instructions to use philschmid/donut-base-finetuned-cord-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/donut-base-finetuned-cord-v2 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="philschmid/donut-base-finetuned-cord-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("philschmid/donut-base-finetuned-cord-v2") model = AutoModelForMultimodalLM.from_pretrained("philschmid/donut-base-finetuned-cord-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Parent(s): 63772ab
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