Instructions to use BadreddineHug/LayoutLMv3_large_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BadreddineHug/LayoutLMv3_large_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BadreddineHug/LayoutLMv3_large_1")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("BadreddineHug/LayoutLMv3_large_1") model = AutoModelForTokenClassification.from_pretrained("BadreddineHug/LayoutLMv3_large_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec8410b664ae6ddd48cb5182f6ac8ecce41a34bc1e590dfcf214a075e2609f9a
- Size of remote file:
- 3.96 kB
- SHA256:
- aa94ca7f3d2fe0d32044cee825df8642536be4687f1885b5158e1b0f2628e0cf
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