Text Classification
Transformers
PyTorch
Safetensors
Russian
bert
russian
classification
sentiment
multiclass
text-embeddings-inference
Instructions to use cointegrated/rubert-tiny-sentiment-balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rubert-tiny-sentiment-balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cointegrated/rubert-tiny-sentiment-balanced")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny-sentiment-balanced") model = AutoModelForSequenceClassification.from_pretrained("cointegrated/rubert-tiny-sentiment-balanced", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (88ecd35a5003c6fd7b1eebc30e4446eb1649702e) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>e0679dd
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initial commit
1eb9f9b