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Mahmoud3899
/
direct

Text Classification
Transformers
Safetensors
deberta-v2
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Mahmoud3899/direct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Mahmoud3899/direct with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Mahmoud3899/direct")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Mahmoud3899/direct")
    model = AutoModelForSequenceClassification.from_pretrained("Mahmoud3899/direct")
  • Notebooks
  • Google Colab
  • Kaggle
direct
749 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Mahmoud3899's picture
Mahmoud3899
Upload tokenizer
d941448 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    5.17 kB
    Upload DebertaV2ForSequenceClassification over 1 year ago
  • added_tokens.json
    23 Bytes
    Upload tokenizer over 1 year ago
  • config.json
    18.3 kB
    Upload DebertaV2ForSequenceClassification over 1 year ago
  • model.safetensors
    738 MB
    xet
    Upload DebertaV2ForSequenceClassification over 1 year ago
  • special_tokens_map.json
    970 Bytes
    Upload tokenizer over 1 year ago
  • spm.model
    2.46 MB
    xet
    Upload tokenizer over 1 year ago
  • tokenizer.json
    8.65 MB
    Upload tokenizer over 1 year ago
  • tokenizer_config.json
    1.47 kB
    Upload tokenizer over 1 year ago