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cvcio
/
roberta-el-ner4

Token Classification
Transformers
PyTorch
Safetensors
Greek
roberta
Generated from Trainer
Greek
ner
Model card Files Files and versions
xet
Community

Instructions to use cvcio/roberta-el-ner4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use cvcio/roberta-el-ner4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="cvcio/roberta-el-ner4")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("cvcio/roberta-el-ner4")
    model = AutoModelForTokenClassification.from_pretrained("cvcio/roberta-el-ner4")
  • Notebooks
  • Google Colab
  • Kaggle

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  • .gitattributes
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    initial commit almost 3 years ago
  • README.md
    5.04 kB
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  • all_results.json
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  • config.json
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  • eval_results.json
    345 Bytes
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  • merges.txt
    1.37 MB
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  • model.safetensors
    496 MB
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  • predict_results.json
    325 Bytes
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  • predictions.txt
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  • pytorch_model.bin
    496 MB
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    3.93 MB
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  • tokenizer_config.json
    378 Bytes
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  • train_results.json
    198 Bytes
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  • trainer_state.json
    22.2 kB
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  • training_args.bin
    3.96 kB
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  • vocab.json
    1.71 MB
    Initial commit almost 3 years ago