Instructions to use DeepPavlov/rubert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepPavlov/rubert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DeepPavlov/rubert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/rubert-base-cased") model = AutoModel.from_pretrained("DeepPavlov/rubert-base-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2df3d760284e9fe289b371d6154493b028fdc4cb7466579840ce1448ea12b5b8
- Size of remote file:
- 714 MB
- SHA256:
- e5691c9cb13c98d396ae2e584f4d01a098fc9416a882425ece4359b807730890
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