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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from cointegrated/rubert-tiny-bilingual-nli: direct link, hf CLI and curl.
- Browser
- Download file 47.1 MB
-
https://huggingface.co/cointegrated/rubert-tiny-bilingual-nli/resolve/main/model.safetensors
- Command line
-
hf download hf://cointegrated/rubert-tiny-bilingual-nli/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/cointegrated/rubert-tiny-bilingual-nli/resolve/main/model.safetensors
47.1 MB
- Xet hash:
- 94438353b3f353a31bdae4dd6e329843785a33ba344b28ff4ccdfeb65a46419c
- Size of remote file:
- 47.1 MB
- SHA256:
- bf08cca45624a7df05977fd8b910f3e6a07a99409ac1bdb6ed3183452c12b31a
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