onyx-dot-app
/

information-content-model

Text Classification

sentence-transformers

generated_from_setfit_trainer

text-embeddings-inference

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jr-onyx commited on Mar 4, 2025

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-# SetFit with sentence-transformers/paraphrase-mpnet-base-v2
 This is a model based on the [SetFit](https://github.com/huggingface/setfit) approach. It is used to identify whether a short text segmant
 contains information that could be useful by itself to answer a RAG-type question. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Sentence Transformer embedding model. A trained [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.

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+# Information Content Classification using SetFit with Base sentence-transformers/paraphrase-mpnet-base-v2
 This is a model based on the [SetFit](https://github.com/huggingface/setfit) approach. It is used to identify whether a short text segmant
 contains information that could be useful by itself to answer a RAG-type question. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Sentence Transformer embedding model. A trained [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.