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7b的reward model, max-length设置为200,推理一条样本 需要90s-150s不等,直接使用开源的7b Reward model, 加载AutoModelForSequenceClassification,单条样本推理时间在1-5s,这个时间几十倍差距太大了。请问是否有优化方法。 我加载模型的代码是按照api里面get_score接口做的,用的load_model函数加载
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7b的reward model, max-length设置为200,推理一条样本 需要90s-150s不等,直接使用开源的7b Reward model, 加载AutoModelForSequenceClassification,单条样本推理时间在1-5s,这个时间几十倍差距太大了。请问是否有优化方法。
我加载模型的代码是按照api里面get_score接口做的,用的load_model函数加载
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The text was updated successfully, but these errors were encountered: