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:
- b9123472d2af3aef3c6d9664633a8274bc378dc0a006cd62af09118fdbf87f32
- Size of remote file:
- 3.38 kB
- SHA256:
- bbcbc06c000e649130652a661cf2b53d6aa8b1c84858d72aaed491344bf0ddb5
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