Instructions to use segment-any-text/sat-12l-sm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use segment-any-text/sat-12l-sm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="segment-any-text/sat-12l-sm")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("segment-any-text/sat-12l-sm", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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Download README.md from segment-any-text/sat-12l-sm: direct link, hf CLI and curl.
- Browser
- Download file 714 Bytes
-
https://huggingface.co/segment-any-text/sat-12l-sm/resolve/main/README.md
- Command line
-
hf download hf://segment-any-text/sat-12l-sm/README.md
-
curl -L -o README.md https://huggingface.co/segment-any-text/sat-12l-sm/resolve/main/README.md
714 Bytes
metadata
license: mit
language:
- multilingual
- am
- ar
- az
- be
- bg
- bn
- ca
- ceb
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hu
- hy
- id
- ig
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lt
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- mt
- my
- ne
- nl
- 'no'
- pa
- pl
- ps
- pt
- ro
- ru
- si
- sk
- sl
- sq
- sr
- sv
- ta
- te
- tg
- th
- tr
- uk
- ur
- uz
- vi
- xh
- yi
- yo
- zh
- zu
library:
- wtpsplit
sat-12l-sm
Model for wtpsplit.
State-of-the-art sentence segmentation with 12 Transfomer layers.
For details, see our Segment any Text paper