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maxwlnd
/
cl_mention_embedding

Feature Extraction
Transformers
Safetensors
English
bert
contrastive-learning
embeddings
political-science
social-groups
clustering
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use maxwlnd/cl_mention_embedding with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="maxwlnd/cl_mention_embedding")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("maxwlnd/cl_mention_embedding", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
cl_mention_embedding
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
MaximilianWeiland
add model card
d1ed19e 27 days ago
  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • README.md
    4.85 kB
    add model card 27 days ago
  • config.json
    191 Bytes
    update config 28 days ago
  • model.safetensors
    438 MB
    xet
    Add model weigths and tokenizer files 29 days ago
  • special_tokens_map.json
    125 Bytes
    Add model weigths and tokenizer files 29 days ago
  • tokenizer.json
    711 kB
    Add model weigths and tokenizer files 29 days ago
  • tokenizer_config.json
    1.22 kB
    Add model weigths and tokenizer files 29 days ago
  • vocab.txt
    232 kB
    Add model weigths and tokenizer files 29 days ago