Instructions to use segment-any-text/sat-3l-sm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use segment-any-text/sat-3l-sm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="segment-any-text/sat-3l-sm")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("segment-any-text/sat-3l-sm", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download training_args.bin from segment-any-text/sat-3l-sm: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/segment-any-text/sat-3l-sm/resolve/main/training_args.bin
- Command line
-
hf download hf://segment-any-text/sat-3l-sm/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/segment-any-text/sat-3l-sm/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 99e8648f5103c26296935b95b291b0d83fef68c40ee84e0f3b9978dddbbc091a
- Size of remote file:
- 4.98 kB
- SHA256:
- 58eb0a87e07b34b1109e2fea44d1727f0be51043aefd0756990efe39e2786ea2
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