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eunyounglee
/
EEVE-LLM2Vec-MNTP-1-quant

Feature Extraction
Transformers
Safetensors
llama
text-embeddings-inference
4-bit precision
bitsandbytes
Model card Files Files and versions
xet
Community

Instructions to use eunyounglee/EEVE-LLM2Vec-MNTP-1-quant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use eunyounglee/EEVE-LLM2Vec-MNTP-1-quant with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="eunyounglee/EEVE-LLM2Vec-MNTP-1-quant")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("eunyounglee/EEVE-LLM2Vec-MNTP-1-quant")
    model = AutoModel.from_pretrained("eunyounglee/EEVE-LLM2Vec-MNTP-1-quant")
  • Notebooks
  • Google Colab
  • Kaggle
EEVE-LLM2Vec-MNTP-1-quant
5.74 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
eunyounglee's picture
eunyounglee
Upload model
5fc0ffa verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    5.18 kB
    Upload tokenizer about 2 years ago
  • config.json
    1.13 kB
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  • model-00001-of-00002.safetensors
    4.97 GB
    xet
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  • model-00002-of-00002.safetensors
    766 MB
    xet
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  • model.safetensors.index.json
    186 kB
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  • special_tokens_map.json
    692 Bytes
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  • tokenizer.json
    2.18 MB
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    2.05 kB
    Upload tokenizer about 2 years ago