Instructions to use BadreddineHug/LayoutLMv3_97_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BadreddineHug/LayoutLMv3_97_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BadreddineHug/LayoutLMv3_97_1")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("BadreddineHug/LayoutLMv3_97_1") model = AutoModelForTokenClassification.from_pretrained("BadreddineHug/LayoutLMv3_97_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71d7deeb3aa876a4727a196558ddc04db537934ad46a8c860097ad7d5882493a
- Size of remote file:
- 3.96 kB
- SHA256:
- b537afe34d7994a8d308b64f39798c3560ed70b61472066ec6b393fb5e7a105f
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