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BM-K
/
KoMiniLM

Feature Extraction
Transformers
PyTorch
Safetensors
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use BM-K/KoMiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BM-K/KoMiniLM with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="BM-K/KoMiniLM")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("BM-K/KoMiniLM")
    model = AutoModel.from_pretrained("BM-K/KoMiniLM")
  • Notebooks
  • Google Colab
  • Kaggle
KoMiniLM
187 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 16 commits
BM-K's picture
BM-K
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
6db74f9 over 2 years ago
  • .gitattributes
    1.23 kB
    Adding `safetensors` variant of this model (#1) over 2 years ago
  • README.md
    4.31 kB
    Update README.md almost 4 years ago
  • config.json
    671 Bytes
    add model almost 4 years ago
  • model.safetensors
    93.1 MB
    xet
    Adding `safetensors` variant of this model (#1) over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    93.2 MB
    xet
    add model almost 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer almost 4 years ago
  • tokenizer.json
    495 kB
    add tokenizer almost 4 years ago
  • tokenizer_config.json
    531 Bytes
    add tokenizer almost 4 years ago
  • vocab.txt
    248 kB
    add tokenizer almost 4 years ago