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oralunal
/
sentiment

Text Classification
Transformers
Safetensors
distilbert
sentiment-analysis
sentiment
synthetic data
multi-class
social-media-analysis
customer-feedback
product-reviews
brand-monitoring
multilingual
πŸ‡ͺπŸ‡Ί
region:eu
Synthetic
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use oralunal/sentiment with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="oralunal/sentiment")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("oralunal/sentiment")
    model = AutoModelForSequenceClassification.from_pretrained("oralunal/sentiment")
  • Notebooks
  • Google Colab
  • Kaggle
sentiment
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
oralunal's picture
oralunal
init
80110ac 6 months ago
  • .gitattributes
    1.52 kB
    initial commit 6 months ago
  • README.md
    9.82 kB
    init 6 months ago
  • config.json
    851 Bytes
    init 6 months ago
  • model.safetensors
    541 MB
    xet
    init 6 months ago
  • special_tokens_map.json
    125 Bytes
    init 6 months ago
  • tokenizer.json
    2.92 MB
    init 6 months ago
  • tokenizer_config.json
    1.2 kB
    init 6 months ago
  • vocab.txt
    996 kB
    init 6 months ago