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")# 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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5fe649395b560a44aa8d1ce34b0725996c3e9540626e2631aa4271421a184be
- Size of remote file:
- 47.2 MB
- SHA256:
- 48b1f5e89858ef1025c0be4324a47e0853b5efb6b96e51b4a2a2aa4f116d9e02
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