Instructions to use BadreddineHug/LayoutLMv3_large_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BadreddineHug/LayoutLMv3_large_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BadreddineHug/LayoutLMv3_large_2")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("BadreddineHug/LayoutLMv3_large_2") model = AutoModelForTokenClassification.from_pretrained("BadreddineHug/LayoutLMv3_large_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c21dad7c07a934ebb2e40f4934bbdf1dafa925f88b6d99a98e42edf6d374fdd
- Size of remote file:
- 3.9 kB
- SHA256:
- ce61bba057007b95740b462c57ea451e7e6ca8472b3d1c004486490e6eb4b630
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