Instructions to use cmarkea/dit-base-layout-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cmarkea/dit-base-layout-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="cmarkea/dit-base-layout-detection")# Load model directly from transformers import AutoImageProcessor, BeitForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("cmarkea/dit-base-layout-detection") model = BeitForSemanticSegmentation.from_pretrained("cmarkea/dit-base-layout-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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library_name: transformers
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license: apache-2.0
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pipeline_tag: image-segmentation
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# DIT-base-layout-detection
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library_name: transformers
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license: apache-2.0
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pipeline_tag: image-segmentation
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datasets:
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- ds4sd/DocLayNet
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# DIT-base-layout-detection
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