Instructions to use BadreddineHug/LayoutLMv3_large_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BadreddineHug/LayoutLMv3_large_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BadreddineHug/LayoutLMv3_large_3")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("BadreddineHug/LayoutLMv3_large_3") model = AutoModelForTokenClassification.from_pretrained("BadreddineHug/LayoutLMv3_large_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10b308ccfec749b193fe5d31276c7f2b84a96bb69e398fa3a43d05c40ead2366
- Size of remote file:
- 504 MB
- SHA256:
- 6f32138e4c8c4953663fbd780edf62824afc8bf2dde9e6cbee3dcc035f4c16ce
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