SetFit with intfloat/multilingual e5 base This is a SetFit model that can be used for Text Classification. This SetFit model uses intfloat/multilingual e5 base as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification. The model has been trained using an efficient few shot learning technique that involves: 1. Fine tuning a Sentence Transformer with contrastive learning. 2. Training a classification head with features from the fine tuned Sentence Transformer. Model Details Model Description Model Type: SetFit Sentence Transformer body: intfloat/multilingual e5 base Classification head: a LogisticRegression instance Maximum Sequence Length: 512 tokens Number of Classes: 12 classes Model Sources Repository: SetFit on GitHub Paper: Efficient Few Shot Learning Without Prompts Blogpost: SetFit: Efficient Few Shot Learning Without Prompts Model Labels Label Examples : : Business 'Atour stock price target raised to 39 by Macquarie By Investing. Atour stock price target raised to 39 by Macquarie' '1 Smart Growth Stock to Buy With Under 100 in August. Upstart is on track to generate over 1 billion in annual revenue for the first time in its history…
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