Serafim 900m Portuguese (PT) Sentence Transformer tuned for Information Retrieval (IR) This is a sentence transformers model: It maps sentences & paragraphs to a 1536 dimensional dense vector space and can be used for tasks like clustering or semantic search. 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 : sentence transformers.datasets.NoDuplicatesDataLoader.NoDuplicatesDataLoader of length 1989040 with parameters: Loss : sentence transformers.losses.GISTEmbedLoss.GISTEmbedLoss with parameters: Parameters of the fit() Method: Full Model Architecture Citing & Authors The article has been presented at EPIA 2024 conference and published by Springer: @InPro…
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