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LinkinShan
/
hanja-wsd-base

Text Classification
Transformers
Safetensors
Korean
xlm-roberta
feature-extraction
korean
hanja
hangul
mixed-script
word-sense-disambiguation
cross-encoder
preview
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use LinkinShan/hanja-wsd-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use LinkinShan/hanja-wsd-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="LinkinShan/hanja-wsd-base")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("LinkinShan/hanja-wsd-base")
    model = AutoModel.from_pretrained("LinkinShan/hanja-wsd-base", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
hanja-wsd-base
1.36 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
LinkinShan's picture
LinkinShan
model card: preview notice, next-version preview results, evaluation correction
94db67f verified 14 days ago
  • data
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  • src
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  • .gitattributes
    1.8 kB
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  • README.md
    13 kB
    model card: preview notice, next-version preview results, evaluation correction 14 days ago
  • config.json
    742 Bytes
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  • eval_e2e.txt
    335 Bytes
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  • eval_records.txt
    286 Bytes
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  • head.pt
    4.88 kB
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  • model.safetensors
    1.11 GB
    xet
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    342 Bytes
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  • training_curves.png
    199 kB
    xet
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