Instructions to use DeepPavlov/rubert-base-cased-sentence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepPavlov/rubert-base-cased-sentence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DeepPavlov/rubert-base-cased-sentence")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/rubert-base-cased-sentence") model = AutoModel.from_pretrained("DeepPavlov/rubert-base-cased-sentence") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c71d14259357255b2d902a3059aeec1a9cd5256694a92686c3e314cf71b7b97
- Size of remote file:
- 711 MB
- SHA256:
- 24030c19536bf7a6755ba6db21f9808336783b4484776a658ffd6f0875b21b0b
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