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do-me
/
jina-embeddings-v2-small-en

Feature Extraction
Transformers.js
ONNX
Transformers
English
bert
fill-mask
PyTorch
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use do-me/jina-embeddings-v2-small-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers.js

    How to use do-me/jina-embeddings-v2-small-en with Transformers.js:

    // npm i @huggingface/transformers
    import { pipeline } from '@huggingface/transformers';
    
    // Allocate pipeline
    const pipe = await pipeline('feature-extraction', 'do-me/jina-embeddings-v2-small-en');
  • Transformers

    How to use do-me/jina-embeddings-v2-small-en with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="do-me/jina-embeddings-v2-small-en", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("do-me/jina-embeddings-v2-small-en", trust_remote_code=True)
    model = AutoModelForMaskedLM.from_pretrained("do-me/jina-embeddings-v2-small-en", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
jina-embeddings-v2-small-en
Ctrl+K
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  • 1 contributor
History: 6 commits
do-me's picture
do-me
Upload model_quantized.onnx
cb61cf9 over 2 years ago
  • onnx
    Upload model_quantized.onnx over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
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  • config.json
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  • quantize_config.json
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    367 Bytes
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  • vocab.txt
    232 kB
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