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:
- 3ee6f5dc33b3da15147d668d09e0ec8b29bd1ae21ad166cca22f7f24e89d8cf8
- Size of remote file:
- 504 MB
- SHA256:
- 7b7d06ef0cbd04e6694f1e56d94ce0ab9f162db9b0f0ecd7cff92621f5972c75
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