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IAmFlyingMonkey
/
roberta-base-model-korean-text-tag-classification

Text Classification
Transformers
PyTorch
Korean
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use IAmFlyingMonkey/roberta-base-model-korean-text-tag-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use IAmFlyingMonkey/roberta-base-model-korean-text-tag-classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="IAmFlyingMonkey/roberta-base-model-korean-text-tag-classification")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("IAmFlyingMonkey/roberta-base-model-korean-text-tag-classification")
    model = AutoModelForSequenceClassification.from_pretrained("IAmFlyingMonkey/roberta-base-model-korean-text-tag-classification")
  • Notebooks
  • Google Colab
  • Kaggle
roberta-base-model-korean-text-tag-classification
2 GB
Ctrl+K
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  • 1 contributor
History: 8 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
cbec803 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    147 Bytes
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  • config.json
    1.04 kB
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  • merges.txt
    456 kB
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  • model.safetensors
    499 MB
    xet
    Adding `safetensors` variant of this model over 1 year ago
  • optimizer.pt
    997 MB
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    init push over 2 years ago
  • pytorch_model.bin
    499 MB
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  • rng_state.pth
    14.2 kB
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  • scheduler.pt
    1.06 kB
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    2.11 MB
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  • tokenizer_config.json
    351 Bytes
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  • trainer_state.json
    1.52 kB
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  • training_args.bin
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  • vocab.json
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