Instructions to use segment-any-text/sat-12l with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use segment-any-text/sat-12l with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="segment-any-text/sat-12l")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("segment-any-text/sat-12l", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download loras/opus100/da/pytorch_model_head.bin from segment-any-text/sat-12l: direct link, hf CLI and curl.
- Browser
- Download file 343 kB
-
https://huggingface.co/segment-any-text/sat-12l/resolve/main/loras/opus100/da/pytorch_model_head.bin
- Command line
-
hf download hf://segment-any-text/sat-12l/loras/opus100/da/pytorch_model_head.bin
-
curl -L -o pytorch_model_head.bin https://huggingface.co/segment-any-text/sat-12l/resolve/main/loras/opus100/da/pytorch_model_head.bin
343 kB
- Xet hash:
- 4eeda18879777cdc933d4337e17c8f5016d9646496234779a91e08b49c2996f2
- Size of remote file:
- 343 kB
- SHA256:
- 8283808cec06db06673111ce29ed7d72cb0d7e9c575342609d5dd7dc7d6ff253
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