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m-gopichand
/
sentiment_roberta

Text Classification
Transformers
Safetensors
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use m-gopichand/sentiment_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use m-gopichand/sentiment_roberta with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="m-gopichand/sentiment_roberta")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("m-gopichand/sentiment_roberta")
    model = AutoModelForSequenceClassification.from_pretrained("m-gopichand/sentiment_roberta")
  • Notebooks
  • Google Colab
  • Kaggle
sentiment_roberta
502 MB
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  • 1 contributor
History: 3 commits
m-gopichand's picture
m-gopichand
Upload tokenizer
1b7ac54 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    5.18 kB
    Upload RobertaForSequenceClassification about 2 years ago
  • config.json
    1.94 kB
    Upload RobertaForSequenceClassification about 2 years ago
  • merges.txt
    456 kB
    Upload tokenizer about 2 years ago
  • model.safetensors
    499 MB
    xet
    Upload RobertaForSequenceClassification about 2 years ago
  • special_tokens_map.json
    964 Bytes
    Upload tokenizer about 2 years ago
  • tokenizer.json
    2.11 MB
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    1.41 kB
    Upload tokenizer about 2 years ago
  • vocab.json
    798 kB
    Upload tokenizer about 2 years ago