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salsabiilashifa11
/
sbert-cv-2

Feature Extraction
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use salsabiilashifa11/sbert-cv-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use salsabiilashifa11/sbert-cv-2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="salsabiilashifa11/sbert-cv-2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("salsabiilashifa11/sbert-cv-2")
    model = AutoModel.from_pretrained("salsabiilashifa11/sbert-cv-2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
sbert-cv-2
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  • 1 contributor
History: 3 commits
salsabiilashifa11's picture
salsabiilashifa11
Upload config.json
b8951db about 3 years ago
  • 1_Pooling
    Upload config.json about 3 years ago
  • .gitattributes
    1.52 kB
    initial commit about 3 years ago
  • config.json
    718 Bytes
    Upload 12 files about 3 years ago
  • config_sentence_transformers.json
    122 Bytes
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  • flax_model.msgpack.msgpack.msgpack
    328 MB
    xet
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  • merges.txt
    456 kB
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  • modules.json
    229 Bytes
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  • pytorch_model.bin
    329 MB
    xet
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    239 Bytes
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  • tf_model.h5.h5.h5
    329 MB
    xet
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  • tokenizer.json
    1.36 MB
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  • tokenizer_config.json
    1.35 kB
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  • vocab.json
    798 kB
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