Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

binhcode25
/
sbert-all-MiniLM-L6-v2-optimum-onnx

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

Instructions to use binhcode25/sbert-all-MiniLM-L6-v2-optimum-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use binhcode25/sbert-all-MiniLM-L6-v2-optimum-onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="binhcode25/sbert-all-MiniLM-L6-v2-optimum-onnx")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("binhcode25/sbert-all-MiniLM-L6-v2-optimum-onnx")
    model = AutoModel.from_pretrained("binhcode25/sbert-all-MiniLM-L6-v2-optimum-onnx")
  • Notebooks
  • Google Colab
  • Kaggle
sbert-all-MiniLM-L6-v2-optimum-onnx
91.3 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 4 commits
nguyenthaibinh
add pooling
eca9b17 almost 2 years ago
  • 1_Pooling
    add pooling almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • config.json
    650 Bytes
    initial commit almost 2 years ago
  • model.onnx
    90.4 MB
    xet
    initial commit almost 2 years ago
  • modules.json
    349 Bytes
    add modules.json almost 2 years ago
  • special_tokens_map.json
    695 Bytes
    initial commit almost 2 years ago
  • tokenizer.json
    712 kB
    initial commit almost 2 years ago
  • tokenizer_config.json
    1.43 kB
    initial commit almost 2 years ago
  • vocab.txt
    232 kB
    initial commit almost 2 years ago