sentence msmarco bert base dot v5 nlpl code search net This is a sentence transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. It has been trained on the with the code search net dataset Usage (Sentence Transformers) Using this model becomes easy when you have sentence transformers installed: Then you can use the model like this: Usage (HuggingFace Transformers) Without sentence transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling operation on top of the contextualized word embeddings. Evaluation Results For an automated evaluation of this model, see the Sentence Embeddings Benchmark : https://seb.sbert.net Training The model was trained with the parameters: DataLoader : torch.utils.data.dataloader.DataLoader of length 39185 with parameters: Loss : sentence transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss with parameters: Parameters of the fit() Method: Full Model Architecture Citing & Authors
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