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- This is a fine-tuned version of BAAI/bge-reranker-base.
 
 
 
 
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  I created a dataset of 89k items, I used a LLM to extract and label relevant information from job adverts description and used the unlabeled data as the negatives.
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  I used the same type of method to extract labels from the LLM by scraping different company websites so I can get labels for e.g product, service and upcoming offerings.
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  license: mit
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+ license: mit
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+ pipeline_tag: text-classification
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+ This is a fine-tuned version of [BAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base).
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  I created a dataset of 89k items, I used a LLM to extract and label relevant information from job adverts description and used the unlabeled data as the negatives.
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  I used the same type of method to extract labels from the LLM by scraping different company websites so I can get labels for e.g product, service and upcoming offerings.
 
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  ---
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  license: mit
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