Instructions to use BadreddineHug/LayoutLMv3_97_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BadreddineHug/LayoutLMv3_97_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BadreddineHug/LayoutLMv3_97_2")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("BadreddineHug/LayoutLMv3_97_2") model = AutoModelForTokenClassification.from_pretrained("BadreddineHug/LayoutLMv3_97_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a034084dacfcf1e2112730025c22602025a6d9e843ad6ed5de6937b7c173a221
- Size of remote file:
- 3.96 kB
- SHA256:
- f21410a0541c99ac5791a24daf6a959a2334f70a9c5183cdd3f386170fb9bccb
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