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nextgeo
/
address-extraction

Token Classification
Transformers
Safetensors
PyTorch
bert
ner
turkish
tr
dbmdz
bert-base-cased
bert-base-turkish-cased
Model card Files Files and versions
xet
Community
1

Instructions to use nextgeo/address-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nextgeo/address-extraction with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="nextgeo/address-extraction")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("nextgeo/address-extraction")
    model = AutoModelForTokenClassification.from_pretrained("nextgeo/address-extraction", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
address-extraction
883 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 10 commits
duoquote
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d1aed23 over 2 years ago
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  • .gitattributes
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  • .gitignore
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  • README.md
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  • config.json
    2.22 kB
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  • environment.yml
    3.33 kB
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  • labels.json
    319 Bytes
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  • model.safetensors
    440 MB
    xet
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  • predict.py
    2.71 kB
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    755 kB
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  • tokenizer_config.json
    1.25 kB
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  • train.py
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  • training_args.bin
    4.66 kB
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  • vocab.txt
    251 kB
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