Zero-Shot Classification
Transformers
PyTorch
Safetensors
Russian
bert
text-classification
rubert
russian
nli
rte
Instructions to use cointegrated/rubert-tiny-bilingual-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rubert-tiny-bilingual-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="cointegrated/rubert-tiny-bilingual-nli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny-bilingual-nli") model = AutoModelForSequenceClassification.from_pretrained("cointegrated/rubert-tiny-bilingual-nli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Update README.md
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (38c824d2cf0be890b60bccf5c1c0ba74b51cbb42) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>ae584da
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Update README.md
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Update README.md
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Create README.md
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The second commit: train longer
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The first commit
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initial commit
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