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Daniel-Sousa
/
outputs

Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use Daniel-Sousa/outputs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Daniel-Sousa/outputs with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Daniel-Sousa/outputs")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Daniel-Sousa/outputs")
    model = AutoModelForSequenceClassification.from_pretrained("Daniel-Sousa/outputs", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
outputs
579 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Daniel-Sousa's picture
Daniel-Sousa
lesson-4
b00bbe6 almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    1.54 kB
    lesson-4 almost 3 years ago
  • added_tokens.json
    23 Bytes
    lesson-4 almost 3 years ago
  • config.json
    958 Bytes
    lesson-4 almost 3 years ago
  • pytorch_model.bin
    568 MB
    xet
    lesson-4 almost 3 years ago
  • special_tokens_map.json
    173 Bytes
    lesson-4 almost 3 years ago
  • spm.model
    2.46 MB
    xet
    lesson-4 almost 3 years ago
  • tokenizer.json
    8.66 MB
    lesson-4 almost 3 years ago
  • tokenizer_config.json
    412 Bytes
    lesson-4 almost 3 years ago
  • training_args.bin
    3.96 kB
    xet
    lesson-4 almost 3 years ago