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AnkitAI
/
Sensible-ModernBERT-Sentiment-Analysis

Text Classification
Transformers
Safetensors
English
modernbert
sentiment-analysis
sentiment
sst-2
sst2
reviews
english
positive-negative
distilbert-sst2-alternative
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use AnkitAI/Sensible-ModernBERT-Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AnkitAI/Sensible-ModernBERT-Sentiment-Analysis with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="AnkitAI/Sensible-ModernBERT-Sentiment-Analysis")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("AnkitAI/Sensible-ModernBERT-Sentiment-Analysis")
    model = AutoModelForSequenceClassification.from_pretrained("AnkitAI/Sensible-ModernBERT-Sentiment-Analysis", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Sensible-ModernBERT-Sentiment-Analysis / eval
3.63 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
AnkitAI's picture
AnkitAI
Upload eval/result.json with huggingface_hub
1ee12c2 verified 2 days ago
  • result.json
    211 Bytes
    Upload eval/result.json with huggingface_hub 2 days ago
  • train_and_eval.py
    3.42 kB
    Upload eval/train_and_eval.py with huggingface_hub 2 days ago