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elishaw
/
deberta_mental

Text Classification
Transformers
Safetensors
PyTorch
English
deberta-v2
mental-health
deberta-v3
sentiment-analysis
healthcare
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use elishaw/deberta_mental with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="elishaw/deberta_mental")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("elishaw/deberta_mental")
    model = AutoModelForSequenceClassification.from_pretrained("elishaw/deberta_mental")
  • Notebooks
  • Google Colab
  • Kaggle
deberta_mental
579 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
elishaw's picture
elishaw
README.md
6cf92cb verified 7 months ago
  • .gitattributes
    1.52 kB
    initial commit 7 months ago
  • README.md
    2.97 kB
    README.md 7 months ago
  • added_tokens.json
    23 Bytes
    Upload folder using huggingface_hub 7 months ago
  • config.json
    1.24 kB
    Upload folder using huggingface_hub 7 months ago
  • model.safetensors
    568 MB
    xet
    Upload folder using huggingface_hub 7 months ago
  • special_tokens_map.json
    286 Bytes
    Upload folder using huggingface_hub 7 months ago
  • spm.model
    2.46 MB
    xet
    Upload folder using huggingface_hub 7 months ago
  • tokenizer.json
    8.66 MB
    Upload folder using huggingface_hub 7 months ago
  • tokenizer_config.json
    1.28 kB
    Upload folder using huggingface_hub 7 months ago