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Severian
/
embed

Feature Extraction
Transformers
PyTorch
Core ML
ONNX
Safetensors
bert
fill-mask
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use Severian/embed with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Severian/embed", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("Severian/embed", trust_remote_code=True)
    model = AutoModelForMaskedLM.from_pretrained("Severian/embed", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
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