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deepset
/
deberta-v3-base-injection

Text Classification
Transformers
PyTorch
Safetensors
English
German
deberta-v2
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Community
9

Instructions to use deepset/deberta-v3-base-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use deepset/deberta-v3-base-injection with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="deepset/deberta-v3-base-injection")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("deepset/deberta-v3-base-injection")
    model = AutoModelForSequenceClassification.from_pretrained("deepset/deberta-v3-base-injection")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
deberta-v3-base-injection
749 MB
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  • 7 contributors
History: 6 commits
librarian-bot's picture
librarian-bot
Librarian Bot: Add base_model information to model
50607ed almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    2.12 kB
    Librarian Bot: Add base_model information to model almost 3 years ago
  • added_tokens.json
    23 Bytes
    upload all about 3 years ago
  • config.json
    996 Bytes
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  • gitattributes.txt
    1.48 kB
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  • gitignore.txt
    13 Bytes
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  • pytorch_model.bin
    738 MB
    xet
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  • special_tokens_map.json
    173 Bytes
    upload all about 3 years ago
  • spm.model
    2.46 MB
    xet
    upload all about 3 years ago
  • tokenizer.json
    8.66 MB
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  • tokenizer_config.json
    412 Bytes
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  • training_args.bin
    3.96 kB
    xet
    upload all about 3 years ago