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yezdata
/
EmCoder

Text Classification
Transformers
Safetensors
English
emcoder
feature-extraction
emotion-recognition
bayesian-deep-learning
mc-dropout
uncertainty-quantification
multi-label-classification
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use yezdata/EmCoder with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="yezdata/EmCoder", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("yezdata/EmCoder", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
EmCoder / emcoder /epoch_5
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
yezdata's picture
yezdata
Upload 61 files
60b66e8 verified 20 days ago
  • model.safetensors
    329 MB
    xet
    Upload 61 files 20 days ago
  • model_config.json
    1.8 kB
    Upload 61 files 20 days ago
  • model_state.json
    80 Bytes
    Upload 61 files 20 days ago
  • tokenizer.json
    1.2 MB
    Upload 61 files 20 days ago
  • tokenizer_config.json
    1.15 MB
    Upload 61 files 20 days ago
  • train_config.json
    245 Bytes
    Upload 61 files 20 days ago