Instructions to use naver-clova-ix/donut-base-finetuned-rvlcdip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naver-clova-ix/donut-base-finetuned-rvlcdip 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-finetuned-rvlcdip")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("naver-clova-ix/donut-base-finetuned-rvlcdip") model = AutoModelForMultimodalLM.from_pretrained("naver-clova-ix/donut-base-finetuned-rvlcdip") - Notebooks
- Google Colab
- Kaggle
Missing feature_extractor_type or wrong model_type
#5 opened over 1 year ago
by
enkaya
Adding `safetensors` variant of this model
#4 opened about 2 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#3 opened almost 3 years ago
by
SFconvertbot
Why `"max_position_embeddings": 8`?
👍 4
#2 opened almost 3 years ago
by
fxmarty