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tmnam20
/
mdeberta-v3-base-mrpc-1

Text Classification
Transformers
Safetensors
English
deberta-v2
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use tmnam20/mdeberta-v3-base-mrpc-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tmnam20/mdeberta-v3-base-mrpc-1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="tmnam20/mdeberta-v3-base-mrpc-1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("tmnam20/mdeberta-v3-base-mrpc-1")
    model = AutoModelForSequenceClassification.from_pretrained("tmnam20/mdeberta-v3-base-mrpc-1")
  • Notebooks
  • Google Colab
  • Kaggle
mdeberta-v3-base-mrpc-1
1.14 GB
Ctrl+K
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  • 1 contributor
History: 14 commits
tmnam20's picture
tmnam20
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  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • all_results.json
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  • config.json
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  • eval_results.json
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  • model.safetensors
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  • special_tokens_map.json
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  • spm.model
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  • tokenizer.json
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  • tokenizer_config.json
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  • train_results.json
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  • trainer_state.json
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  • training_args.bin
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