Instructions to use imenrebhi/LayoutLMv2-model-pfe2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imenrebhi/LayoutLMv2-model-pfe2 with Transformers:
# Load model directly from transformers import AutoProcessor, LayoutLMv2ForRelationExtraction processor = AutoProcessor.from_pretrained("imenrebhi/LayoutLMv2-model-pfe2") model = LayoutLMv2ForRelationExtraction.from_pretrained("imenrebhi/LayoutLMv2-model-pfe2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b265d0a3b529a55bc764a799a0da2eabe42ac84b894ae507169a6bdabf8697b
- Size of remote file:
- 1.49 GB
- SHA256:
- 7c57143bb1b856ed7248862f13c630bfe92821313055874c2f146119a8631559
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