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eternalGenius
/
rubert_level1_v2

Text Classification
Transformers
Safetensors
Russian
bert
multilabel-classification
requirements-engineering
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use eternalGenius/rubert_level1_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use eternalGenius/rubert_level1_v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="eternalGenius/rubert_level1_v2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("eternalGenius/rubert_level1_v2")
    model = AutoModelForSequenceClassification.from_pretrained("eternalGenius/rubert_level1_v2")
  • Notebooks
  • Google Colab
  • Kaggle
rubert_level1_v2
715 MB
Ctrl+K
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  • 1 contributor
History: 9 commits
eternalGenius's picture
eternalGenius
Update thresholds.json
7340982 verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    3.6 kB
    Update README.md 4 months ago
  • config.json
    1.11 kB
    rubert_level1_v2: F1 micro=0.975, F1 macro=0.975 4 months ago
  • model.safetensors
    711 MB
    xet
    rubert_level1_v2: F1 micro=0.975, F1 macro=0.975 4 months ago
  • thresholds.json
    367 Bytes
    Update thresholds.json 4 months ago
  • tokenizer.json
    3.57 MB
    Upload tokenizer 4 months ago
  • tokenizer_config.json
    351 Bytes
    Upload tokenizer 4 months ago
  • training_args.bin
    5.2 kB
    xet
    rubert_level1_v2: F1 micro=0.975, F1 macro=0.975 4 months ago