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
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hypothesis_template: "Тема текста - {}."
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# RuBERT-tiny for NLI (natural language inference)
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- rte
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- zero-shot-classification
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widget:
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- text: "Какая гадость эта ваша заливная рыба!"
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candidate_labels: "я доволен, я не доволен"
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# RuBERT-tiny for NLI (natural language inference)
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