SaT Supervised Mixture (SM) Models
Collection
SaT (Segment any Text) models, further trained on a Supervised Mixture of diverse styles and corruptions. Universal Sentence Segmentation models! • 6 items • Updated • 5
# Load model directly
from transformers import AutoModelForTokenClassification
model = AutoModelForTokenClassification.from_pretrained("segment-any-text/sat-3l-sm", dtype="auto")Quick Links
sat-3l-sm
Model for wtpsplit.
State-of-the-art sentence segmentation with 3 Transfomer layers.
For details, see our Segment any Text paper
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="segment-any-text/sat-3l-sm")