Zero-Shot Classification
Transformers
PyTorch
Safetensors
Russian
bert
text-classification
rubert
russian
nli
rte
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-base-cased-nli-twoway")
model = AutoModelForSequenceClassification.from_pretrained("cointegrated/rubert-base-cased-nli-twoway", device_map="auto")Quick Links
RuBERT for NLI (natural language inference)
This is the DeepPavlov/rubert-base-cased fine-tuned to predict the logical relationship between two short texts: entailment or not entailment.
For more details, see the card for a similar model: https://huggingface.co/cointegrated/rubert-base-cased-nli-threeway
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="cointegrated/rubert-base-cased-nli-twoway")