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nasa-impact
/
tdamm-classification

Text Classification
Transformers
Safetensors
English
bert
Text Classification
TDAMM
Multi-label Classification
NASA
Astrophysics
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use nasa-impact/tdamm-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nasa-impact/tdamm-classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="nasa-impact/tdamm-classification")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("nasa-impact/tdamm-classification")
    model = AutoModelForSequenceClassification.from_pretrained("nasa-impact/tdamm-classification")
  • Notebooks
  • Google Colab
  • Kaggle
tdamm-classification
437 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 21 commits
bishwaspraveen's picture
bishwaspraveen
Update README.md
1477943 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    2.33 kB
    Update README.md over 1 year ago
  • config.json
    3.91 kB
    Updated label to id mapping in config over 1 year ago
  • model.safetensors
    436 MB
    xet
    Add model from wandb - run astroBERT-80-epochs over 1 year ago
  • model_architecture.txt
    1.81 kB
    Add model from wandb - run astroBERT-80-epochs over 1 year ago
  • special_tokens_map.json
    695 Bytes
    Added special tokens map over 1 year ago
  • tokenizer.json
    679 kB
    Added tokenizer over 1 year ago
  • tokenizer_config.json
    1.37 kB
    Added tokenizer configuration over 1 year ago
  • training_args.bin

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    167 Bytes
    xet
    Added training arguments over 1 year ago