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liujiarik
/
lim_base_zh

Feature Extraction
Transformers
PyTorch
bert
mteb
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use liujiarik/lim_base_zh with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="liujiarik/lim_base_zh")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("liujiarik/lim_base_zh")
    model = AutoModel.from_pretrained("liujiarik/lim_base_zh")
  • Notebooks
  • Google Colab
  • Kaggle
lim_base_zh
410 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
liujiarik's picture
liujiarik
Update README.md
8434461 over 2 years ago
  • 1_Pooling
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  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    8.76 kB
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  • config.json
    959 Bytes
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  • config_sentence_transformers.json
    124 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.LongStorage",
    • "torch.FloatStorage"

    What is a pickle import?

    409 MB
    xet
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    439 kB
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  • tokenizer_config.json
    530 Bytes
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  • vocab.txt
    110 kB
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