Instructions to use vikp/layout_segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikp/layout_segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vikp/layout_segmenter")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("vikp/layout_segmenter") model = AutoModelForTokenClassification.from_pretrained("vikp/layout_segmenter") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d7e6cf6a98ccbe9bb0a1e951aa5e251f860b653b67e38849b5cfcd88d3f7db2
- Size of remote file:
- 504 MB
- SHA256:
- 5d522d4812009bb5b1f9ba6344b709f3b31873e97f5aa2c368dfce10d386b222
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