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:
- 87b8f66746dd14e97c8dbed7b7911b118f1986ad540ceee0aa1dae3a89bfc4e8
- Size of remote file:
- 504 MB
- SHA256:
- 446eb28f2c1898afa8309e641e1da73f8b1fbae5feeab161d71ffaed82c9e9bc
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