Instructions to use sahil-everlign/layoutlmv2-document-classification-rvl-cdip-oneperlabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sahil-everlign/layoutlmv2-document-classification-rvl-cdip-oneperlabel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sahil-everlign/layoutlmv2-document-classification-rvl-cdip-oneperlabel")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("sahil-everlign/layoutlmv2-document-classification-rvl-cdip-oneperlabel") model = AutoModelForSequenceClassification.from_pretrained("sahil-everlign/layoutlmv2-document-classification-rvl-cdip-oneperlabel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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