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Sumedhzz
/
Sentiment-Analyzer-Quantized

Text Classification
Transformers
ONNX
xlm-roberta
hinglish
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Sumedhzz/Sentiment-Analyzer-Quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Sumedhzz/Sentiment-Analyzer-Quantized with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Sumedhzz/Sentiment-Analyzer-Quantized")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Sumedhzz/Sentiment-Analyzer-Quantized")
    model = AutoModelForSequenceClassification.from_pretrained("Sumedhzz/Sentiment-Analyzer-Quantized")
  • Notebooks
  • Google Colab
  • Kaggle
Sentiment-Analyzer-Quantized
296 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 13 commits
Sumedh satish gajbhiye
Update README.md
1ea05bd verified about 1 month ago
  • .gitattributes
    1.57 kB
    Upload 6 files about 1 month ago
  • README.md
    112 Bytes
    Update README.md about 1 month ago
  • config.json
    922 Bytes
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  • handler.py
    448 Bytes
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  • model.onnx
    279 MB
    xet
    Rename model_quantized.onnx to model.onnx about 1 month ago
  • ort_config.json
    796 Bytes
    Upload 6 files about 1 month ago
  • requirements.txt
    32 Bytes
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  • runtime.txt
    11 Bytes
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  • special_tokens_map.json
    1.02 kB
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  • tokenizer.json
    16.8 MB
    xet
    Upload 6 files about 1 month ago
  • tokenizer_config.json
    1.51 kB
    Upload 6 files about 1 month ago