Zero-Shot Classification
Transformers
PyTorch
Safetensors
Russian
bert
text-classification
rubert
russian
nli
rte
Instructions to use cointegrated/rubert-base-cased-nli-twoway with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rubert-base-cased-nli-twoway with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="cointegrated/rubert-base-cased-nli-twoway")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af0e9b56f814443b9e161af1f2612a04f316ef3bb53e69f8fa0400d0e7e05960
- Size of remote file:
- 712 MB
- SHA256:
- 4d3706057de3ac17f84ea6ca817f13eaef0059abeb30533c682580b2f254281f
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