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")# 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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21e6faa540a2d0d2a0920d2cca6e5c5d3f05e4a9d289ea0bd24962b816d33e79
- Size of remote file:
- 47.2 MB
- SHA256:
- a934e2a785ab24e55cf1dd532f51daff7b91a18867683ab80475d89ee67ca867
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