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tabularisai
/
robust-sentiment-analysis

Text Classification
Transformers
Safetensors
English
distilbert
sentiment-analysis
sentiment
synthetic data
multi-class
social-media-analysis
customer-feedback
product-reviews
brand-monitoring
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use tabularisai/robust-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tabularisai/robust-sentiment-analysis with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="tabularisai/robust-sentiment-analysis")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("tabularisai/robust-sentiment-analysis")
    model = AutoModelForSequenceClassification.from_pretrained("tabularisai/robust-sentiment-analysis")
  • Notebooks
  • Google Colab
  • Kaggle
robust-sentiment-analysis
269 MB
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  • 2 contributors
History: 43 commits
vdmbrsv's picture
vdmbrsv
Update README.md
c542a28 verified 9 months ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    10 kB
    Update README.md 9 months ago
  • config.json
    819 Bytes
    Update config.json about 1 year ago
  • model.safetensors
    268 MB
    xet
    Upload DistilBertForSequenceClassification over 1 year ago
  • quantize_config.json
    722 Bytes
    Upload quantize_config.json with huggingface_hub almost 2 years ago
  • special_tokens_map.json
    125 Bytes
    Upload tokenizer almost 2 years ago
  • tokenizer.json
    711 kB
    Upload tokenizer almost 2 years ago
  • tokenizer_config.json
    1.2 kB
    Upload tokenizer over 1 year ago
  • vocab.txt
    232 kB
    Upload tokenizer almost 2 years ago