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isy-thl
/
multilingual-e5-base-course-skill-tuned

Sentence Similarity
sentence-transformers
TensorBoard
ONNX
Safetensors
German
xlm-roberta
information retrieval
education
competency
course
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use isy-thl/multilingual-e5-base-course-skill-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use isy-thl/multilingual-e5-base-course-skill-tuned with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("isy-thl/multilingual-e5-base-course-skill-tuned")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Notebooks
  • Google Colab
  • Kaggle
multilingual-e5-base-course-skill-tuned / onnx
1.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
pascalhuerten's picture
pascalhuerten
Update onnx files
483f0e5 verified almost 2 years ago
  • config.json
    799 Bytes
    Update onnx files almost 2 years ago
  • model.onnx
    1.11 GB
    xet
    Update onnx files almost 2 years ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    Upload onnx model files almost 2 years ago
  • special_tokens_map.json
    1.02 kB
    Upload onnx model files almost 2 years ago
  • tokenizer.json
    17.1 MB
    xet
    Upload onnx model files almost 2 years ago
  • tokenizer_config.json
    1.23 kB
    Upload onnx model files almost 2 years ago