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segment-any-text
/
sat-9l

Token Classification
Transformers
PyTorch
ONNX
xlm-token
Model card Files Files and versions
xet
Community
1

Instructions to use segment-any-text/sat-9l with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use segment-any-text/sat-9l with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="segment-any-text/sat-9l")
    # Load model directly
    from transformers import AutoModelForTokenClassification
    model = AutoModelForTokenClassification.from_pretrained("segment-any-text/sat-9l", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • sat-9l

sat-9l

Model for wtpsplit.

State-of-the-art sentence segmentation with 9 Transfomer layers.

For details, see our Segment any Text paper

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Sven33/SATEv1.5

Collection including segment-any-text/sat-9l

SaT Base Models

Collection
Base SaT (Segment any Text) models, to be used for sentence and paragraph segmentation. Easily adaptable via LoRA. • 6 items • Updated Jun 26, 2024 • 3

Paper for segment-any-text/sat-9l

Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence Segmentation

Paper • 2406.16678 • Published Jun 24, 2024 • 16
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