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nasa-impact
/
tdamm-classification-v2

Text Classification
Transformers
Safetensors
English
roberta
Text Classification
TDAMM
Multi-label Classification
NASA
Astrophysics
Science Document Entity
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use nasa-impact/tdamm-classification-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nasa-impact/tdamm-classification-v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="nasa-impact/tdamm-classification-v2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("nasa-impact/tdamm-classification-v2")
    model = AutoModelForSequenceClassification.from_pretrained("nasa-impact/tdamm-classification-v2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
tdamm-classification-v2
504 MB
Ctrl+K
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  • 2 contributors
History: 8 commits
nishparadox's picture
nishparadox
ksmu's picture
ksmu
update config.json to include mappings (#2)
80844d9 verified 7 months ago
  • .gitattributes
    1.52 kB
    initial commit 7 months ago
  • README.md
    3.74 kB
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  • config.json
    2.61 kB
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  • merges.txt
    476 kB
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  • model.safetensors
    500 MB
    xet
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  • model_architecture.txt
    1.85 kB
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    2.15 MB
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  • tokenizer_config.json
    413 Bytes
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  • training_args.bin
    5.37 kB
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  • vocab.json
    817 kB
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