Instructions to use henrydz/layoutlmv3-document-classification-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henrydz/layoutlmv3-document-classification-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henrydz/layoutlmv3-document-classification-v1")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("henrydz/layoutlmv3-document-classification-v1") model = AutoModelForSequenceClassification.from_pretrained("henrydz/layoutlmv3-document-classification-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c9e240d07d356ced1adc4a4f4e680fd93c76383de943360bb70647671ae4e2f
- Size of remote file:
- 504 MB
- SHA256:
- 0fa8ea42fca998d7b0089464f2fa2777b950274aa87bca611a28f088ad1dffef
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