Instructions to use segment-any-text/sat-1l with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use segment-any-text/sat-1l with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="segment-any-text/sat-1l")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("segment-any-text/sat-1l", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9ada27b1211182f9fd289ea265ab2d0b62bc3801adf0226dc69358dda8cb11f
- Size of remote file:
- 3.9 kB
- SHA256:
- c03a37c4ffc3d28909b7cc4e43f3fcb960a1c33451f7498aebb3dc38cacbf857
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.