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新人求助,能提供bert,pythonAPI推理部署示例嘛,我该如何做前处理和后处理。
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如果是口语理解(Spoken Language Understanding,SLU)任务可以参考 https://github.com/PaddlePaddle/PaddleNLP/blob/develop/model_zoo/ernie-3.0-tiny/deploy/cpp/infer_demo.cc 或 https://github.com/hong19860320/PaddleLite-generic-demo/blob/55c8f7936e6e1c40231c5c9472c5251891a9ae01/spoken_language_understanding_demo/shell/demo.cc#L344 ,需要注意的是 tokenizer 使用了 PaddleNLP 的 fast_tokenizer 加速库 https://github.com/PaddlePaddle/PaddleNLP/tree/develop/fast_tokenizer 。 不同任务前、后处理差异都比较大,可以参考 PaddleNLP repo 相关示例 https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo 自行编写代码。
感谢!
hong19860320
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新人求助,能提供bert,pythonAPI推理部署示例嘛,我该如何做前处理和后处理。
The text was updated successfully, but these errors were encountered: