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Aniemore
/
rubert-tiny2-russian-emotion-detection

Text Classification
Transformers
PyTorch
Safetensors
Russian
bert
russian
classification
emotion
emotion-detection
emotion-recognition
multilabel
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use Aniemore/rubert-tiny2-russian-emotion-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Aniemore/rubert-tiny2-russian-emotion-detection with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Aniemore/rubert-tiny2-russian-emotion-detection")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Aniemore/rubert-tiny2-russian-emotion-detection")
    model = AutoModelForSequenceClassification.from_pretrained("Aniemore/rubert-tiny2-russian-emotion-detection", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
rubert-tiny2-russian-emotion-detection / assets
6.89 kB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 1 commit
Ar4ikov's picture
Ar4ikov
Model card with measured CEDR-M7 results; usage examples unchanged
dfa4b65 verified 18 days ago
  • per_class.svg
    4.28 kB
    Model card with measured CEDR-M7 results; usage examples unchanged 18 days ago
  • summary.svg
    2.61 kB
    Model card with measured CEDR-M7 results; usage examples unchanged 18 days ago