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mxlcw
/
rubert-tiny2-russian-financial-sentiment

Text Classification
Transformers
Safetensors
Russian
bert
sentiment-analysis
multi-class-classification
financial
telegram
rubert
sentiment
tiny
russian
multiclass
classification
Text Classification
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use mxlcw/rubert-tiny2-russian-financial-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mxlcw/rubert-tiny2-russian-financial-sentiment with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="mxlcw/rubert-tiny2-russian-financial-sentiment")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("mxlcw/rubert-tiny2-russian-financial-sentiment")
    model = AutoModelForSequenceClassification.from_pretrained("mxlcw/rubert-tiny2-russian-financial-sentiment")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
rubert-tiny2-russian-financial-sentiment
120 MB
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  • 2 contributors
History: 12 commits
mxlcw's picture
mxlcw
Update README.md
a02913e verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    3.62 kB
    Update README.md over 1 year ago
  • config.json
    922 Bytes
    Upload BertForSequenceClassification almost 2 years ago
  • model.safetensors
    117 MB
    xet
    Upload BertForSequenceClassification almost 2 years ago
  • special_tokens_map.json
    695 Bytes
    Upload tokenizer almost 2 years ago
  • tokenizer.json
    2.41 MB
    Upload tokenizer almost 2 years ago
  • tokenizer_config.json
    1.34 kB
    Upload tokenizer almost 2 years ago
  • vocab.txt
    1.08 MB
    Upload tokenizer almost 2 years ago