upskyy/bge m3 korean This model is korsts and kornli finetuning model from BAAI/bge m3. It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. Model Details Model Description Model Type: Sentence Transformer Base model: BAAI/bge m3 Maximum Sequence Length: 8192 tokens Output Dimensionality: 1024 tokens Similarity Function: Cosine Similarity Full Model Architecture Usage Usage (Sentence Transformers) First install the Sentence Transformers library: Then you can load this model and run inference. 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 Metrics Semantic Similarity Dataset: sts dev Evaluated with EmbeddingSimilarityEvaluator Metric Value : : pearson cosine 0.874 spearman cosine 0.8724 pearson manhattan 0.8593 spearman manhattan 0.8688 pearson euclidean 0.8598 spearman euclidean 0.8694 pearson dot 0.8684 spearman dot 0.8666 p…
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