lightblue/reranker_continuous_filt_max7_train

Reranker training data This data was generated using 4 steps: We gathered queries and corresponding text data from 35 high quality datasets covering more than 95 languages. For datasets which did not already have negative texts for queries, we mined hard negatives using the BAAI/bge-m3 embedding model. For each query, we selected one positive and one negative text and used Qwen/Qwen2.5-32B-Instruct-GPTQ-Int4 to rate the relatedness of each query-text pair using a token "1", "2"… See the full description on the dataset page: https://huggingface.co/datasets/lightblue/reranker_continuous_filt_max

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