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")# 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
- Xet hash:
- 0ccaf6d7f48898c0de2fd0707cb5a5b648575739d63fce07f69a126cf25972a1
- Size of remote file:
- 556 MB
- SHA256:
- 0bb8cf275f98e1c337138bcecdf007876fb2a2b0eb4b5756ce627b2b0510c2c7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.