Example

>>> from transformers import pipeline

>>> pipe = pipeline("text-classification", model="roundspecs/minilm-finetuned-intent-classification")
>>> pipe("smartphone for gaming under 5090")
    [{'label': 'semantic', 'score': 0.8665100932121277}]

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Model size

33.4M params

Tensor type

F32

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Text Classification

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Model tree for roundspecs/minilm-finetuned-intent-classification

Base model

microsoft/MiniLM-L12-H384-uncased

Finetuned

(89)

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roundspecs
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minilm-finetuned-intent-classification

Example

Model tree for roundspecs/minilm-finetuned-intent-classification

Dataset used to train roundspecs/minilm-finetuned-intent-classification