Instructions to use cointegrated/rubert-tiny2-sentence-compression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rubert-tiny2-sentence-compression with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cointegrated/rubert-tiny2-sentence-compression")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny2-sentence-compression") model = AutoModelForTokenClassification.from_pretrained("cointegrated/rubert-tiny2-sentence-compression", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc01b7bc2d6f1d4833f117bdf1e3e73c2626765361b7c683a514afcff0645dd5
- Size of remote file:
- 116 MB
- SHA256:
- e5e075a4e8bc398eca4af6eca352611edbebe5b93ff068ee7a53e86fbd453bbc
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