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Integer-Ctrl
/
cross-encoder-bert-tiny-1gb-bs32

Text Classification
Transformers
Safetensors
bert
text-embeddings-inference
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xet
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1

Instructions to use Integer-Ctrl/cross-encoder-bert-tiny-1gb-bs32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

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    How to use Integer-Ctrl/cross-encoder-bert-tiny-1gb-bs32 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Integer-Ctrl/cross-encoder-bert-tiny-1gb-bs32")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Integer-Ctrl/cross-encoder-bert-tiny-1gb-bs32")
    model = AutoModelForSequenceClassification.from_pretrained("Integer-Ctrl/cross-encoder-bert-tiny-1gb-bs32")
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Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`

#1 opened about 1 year ago by
tomaarsen
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