Recommend switching to newest BAAI/bge small en v1.5, which has more reasonable similarity distribution and same method of usage. FlagEmbedding Model List FAQ Usage Evaluation Train Citation License More details please refer to our Github: FlagEmbedding. English 中文 FlagEmbedding focus on retrieval augmented LLMs, consisting of following projects currently: Fine tuning of LM : LM Cocktail Dense Retrieval : LLM Embedder, BGE Embedding, C MTEB Reranker Model : BGE Reranker News 11/23/2023: Release LM Cocktail, a method to maintain general capabilities during fine tuning by merging multiple language models. Technical Report :fire: 10/12/2023: Release LLM Embedder, a unified embedding model to support diverse retrieval augmentation needs for LLMs. Technical Report 09/15/2023: The technical report of BGE has been released 09/15/2023: The massive training data of BGE has been released 09/12/2023: New models: New reranker model : release cross encoder models BAAI/bge reranker base and BAAI/bge reranker large , which are more powerful than embedding model. We recommend to use/fine tune them to re rank top k documents returned by embedding models. update embedding model : release bge v1.5 em…
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