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ndiy
/
ASPECT_SENT

Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

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

  • Libraries
  • Transformers

    How to use ndiy/ASPECT_SENT with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ndiy/ASPECT_SENT")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("ndiy/ASPECT_SENT")
    model = AutoModelForSequenceClassification.from_pretrained("ndiy/ASPECT_SENT")
  • Notebooks
  • Google Colab
  • Kaggle
ASPECT_SENT / runs
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
ndiy's picture
ndiy
End of training
4035715 verified about 2 years ago
  • May09_14-24-07_5b9fd1c07f62
    End of training about 2 years ago
  • May09_14-26-04_5b9fd1c07f62
    End of training about 2 years ago
  • May09_14-27-13_5b9fd1c07f62
    End of training about 2 years ago
  • May09_14-28-39_5b9fd1c07f62
    End of training about 2 years ago
  • May09_14-30-56_5b9fd1c07f62
    End of training about 2 years ago
  • May09_14-34-23_5b9fd1c07f62
    End of training about 2 years ago
  • May09_15-39-40_21646139398c
    End of training about 2 years ago
  • May13_10-42-56_d9a5d6f3716c
    End of training about 2 years ago