FlagEmbedding For more details please refer to our Github: FlagEmbedding. BGE Multilingual Gemma2 is a LLM based multilingual embedding model. It is trained on a diverse range of languages and tasks based on google/gemma 2 9b. BGE Multilingual Gemma2 primarily demonstrates the following advancements: Diverse training data: The model's training data spans a broad range of languages, including English, Chinese, Japanese, Korean, French, and more.Additionally, the data covers a variety of task types, such as retrieval, classification, and clustering. Outstanding performance: The model exhibits state of the art (SOTA) results on multilingual benchmarks like MIRACL, MTEB pl, and MTEB fr. It also achieves excellent performance on other major evaluations, including MTEB, C MTEB and AIR Bench. 📑 Open source Plan [x] Checkpoint [x] Training Data The training data of BGE Multilingual Gemma2 is available at this link. Usage Using FlagEmbedding By default, FlagLLMModel will use all available GPUs when encoding. Please set os.environ["CUDA VISIBLE DEVICES"] to select specific GPUs. You also can set os.environ["CUDA VISIBLE DEVICES"]="" to make all GPUs unavailable. Using Sentence Transformers…
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