Instructions to use AlexMaclean/sentence-compression-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexMaclean/sentence-compression-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AlexMaclean/sentence-compression-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AlexMaclean/sentence-compression-roberta") model = AutoModelForTokenClassification.from_pretrained("AlexMaclean/sentence-compression-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AlexMaclean/sentence-compression-roberta: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/AlexMaclean/sentence-compression-roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AlexMaclean/sentence-compression-roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AlexMaclean/sentence-compression-roberta/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- ddd46ada10ca3567620c328b8cd37f2c74702b14558ca2f9794d62b950172072
- Size of remote file:
- 496 MB
- SHA256:
- 3fc2ff7b0a17523c2d6c4e8dd2f196b6bfd807ca23119e6851bf068ba05106a4
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