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almugabo
/
review_classifier

Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
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  1. README.md +6 -2
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  base_model: sentence-transformers/paraphrase-mpnet-base-v2
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  ---
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- # SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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- This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. 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 [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
 
 
 
 
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  The model has been trained using an efficient few-shot learning technique that involves:
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  base_model: sentence-transformers/paraphrase-mpnet-base-v2
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  ---
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+ # Review classifier
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+ This model is a text classification model which, when given abstract of a paper, will indicate it if it is a review (1) or not (0).
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+ It is based om [SetFit](https://github.com/huggingface/setfit) model and uses the [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Sentence Transformer embedding model.
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+ A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
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  The model has been trained using an efficient few-shot learning technique that involves:
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