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Labib11
/
MUG-B-1.6-onnx

Feature Extraction
Transformers
ONNX
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Labib11/MUG-B-1.6-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Labib11/MUG-B-1.6-onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Labib11/MUG-B-1.6-onnx", device_map="auto")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Labib11/MUG-B-1.6-onnx")
    model = AutoModel.from_pretrained("Labib11/MUG-B-1.6-onnx", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
MUG-B-1.6-onnx
1.34 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Labib11's picture
Labib11
Upload model.onnx
77c31d4 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    33 Bytes
    initial commit about 2 years ago
  • config.json
    660 Bytes
    Upload 5 files about 2 years ago
  • model.onnx
    1.34 GB
    xet
    Upload model.onnx about 2 years ago
  • special_tokens_map.json
    695 Bytes
    Upload 5 files about 2 years ago
  • tokenizer.json
    711 kB
    Upload 5 files about 2 years ago
  • tokenizer_config.json
    1.24 kB
    Upload 5 files about 2 years ago
  • vocab.txt
    232 kB
    Upload 5 files about 2 years ago