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slxhere
/
modern_ancientpoem_encoder

Sentence Similarity
sentence-transformers
Safetensors
Chinese
bert
feature-extraction
Generated from Trainer
dataset_size:225000
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use slxhere/modern_ancientpoem_encoder with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("slxhere/modern_ancientpoem_encoder")
    
    sentences = [
        "下班后和同事直奔常去的那家火锅店,热热闹闹地涮了一晚上。",
        "联延掩四远,赫弈成洪炉。",
        "把酒仰问天,古今谁不死。",
        "骑出平阳里,筵开卫尉家。"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
modern_ancientpoem_encoder / 2_Dense
7.35 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
slxhere's picture
slxhere
Upload folder using huggingface_hub
992a607 verified about 1 year ago
  • config.json
    116 Bytes
    Upload folder using huggingface_hub about 1 year ago
  • model.safetensors
    7.35 MB
    xet
    Upload folder using huggingface_hub about 1 year ago