AI is happening. The future is updating.BGE-m3-ko
This is a sentence-transformers model trained on the train_set dataset. 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. - Learning other languages besides Chinese and English is insufficient, so additional learning is needed to optimize use of other languages. - This model is additionally trained on the Korean dataset. - **Model Type:** Sentence Transformer Transformer Encoder - **Maximum Sequence Length:** 8192 tokens - **Output Dimensionality:** 1024 tokens - **Similarity Function:** Cosine Similarity
This is a sentence-transformers model trained on the train_set dataset. 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. - Learning other languages besides Chinese and English is insufficient, so additional learning is needed to optimize use of other languages. - This model is additionally trained on the Korean dataset. - **Model Type:** Sentence Transformer Transformer Encoder - **Maximum Sequence Length:** 8192 tokens - **Output Dimensionality:** 1024 tokens - **Similarity Function:** Cosine Similarity