Instructions to use segment-any-text/sat-6l-sm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use segment-any-text/sat-6l-sm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="segment-any-text/sat-6l-sm")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("segment-any-text/sat-6l-sm", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84e429ebe0922868dcf9c4a17085dc2c8c5fa5b72f4e5d82e6aab8c6c875acc7
- Size of remote file:
- 471 MB
- SHA256:
- 6fb1752cdb9959895cd84c73e04f7a93fcb4adf15d2802f26666f5c45abdfa4b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.