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Update Search_reranking_with_cross-encoders.ipynb (#1060)

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Elmira Ghorbani 2024-02-23 23:13:31 +03:30 committed by GitHub
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examples/Search_reranking_with_cross-encoders.ipynb
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"\n", "\n",
"There is also a latency impact of using ```text-davinci-003``` that you'll need to consider, with even our few examples above taking a couple seconds each - again, the ```Fine-tuning``` endpoint may help you here if you are able to get decent results from an ```ada``` or ```babbage``` fine-tuned model.\n", "There is also a latency impact of using ```text-davinci-003``` that you'll need to consider, with even our few examples above taking a couple seconds each - again, the ```Fine-tuning``` endpoint may help you here if you are able to get decent results from an ```ada``` or ```babbage``` fine-tuned model.\n",
"\n", "\n",
"We've used the ```Completions``` endpoint from OpenAI to build our cross-encoder, but this area is well-served by the open-source community. [Here](https://huggingface.co/cross-encoder/mmarco-mMiniLMv2-L12-H384-v1) is an example from HuggingFace, for example.\n", "We've used the ```Completions``` endpoint from OpenAI to build our cross-encoder, but this area is well-served by the open-source community. [Here](https://huggingface.co/jeffwan/mmarco-mMiniLMv2-L12-H384-v1) is an example from HuggingFace, for example.\n",
"\n", "\n",
"We hope you find this useful for tuning your search use cases, and look forward to seeing what you build." "We hope you find this useful for tuning your search use cases, and look forward to seeing what you build."
] ]