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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/rubert-base-cased") model = AutoModel.from_pretrained("DeepPavlov/rubert-base-cased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from DeepPavlov/rubert-base-cased: direct link, hf CLI and curl.
- Browser
- Download file 714 MB
-
https://huggingface.co/DeepPavlov/rubert-base-cased/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://DeepPavlov/rubert-base-cased/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/DeepPavlov/rubert-base-cased/resolve/main/flax_model.msgpack
714 MB
- Xet hash:
- d752d2aba8aab987e60d5cbf789df62cb34a3b4dbe0e6f92a8a20f2a36245134
- Size of remote file:
- 714 MB
- SHA256:
- 8da346601df87881d568b074d00dd9346ef528b3b77edcf57f2d5ed682256902
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