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求助:如何通过微调提升模型的text2sql能力?
当前给出一个建表语句(比如一张用户登录日志表),再问一个问题(比如 当天的DAU是多少), chatglm会给出错误的sql语句。 比如加了一些无关的字段、sql关键字之间没有空格、用户没有去重等
期望通过微调,提升模型的text2sql能力。
期望注入:
问题:
输出: select count(distinct yourid) from your_table where date = today()
从your_table表查询XX的DAU, 以yourid字段作为用户的唯一标识,以date字段作为过滤时间。通过count(distinct yourid)进行去重统计,date=today() 指定为今天。
The text was updated successfully, but these errors were encountered:
我也想知道,有没有大佬指导下
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可以关注一下DB-GPT-HUB项目,https://github.com/csunny/DB-GPT-Hub
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求助:如何通过微调提升模型的text2sql能力?
当前给出一个建表语句(比如一张用户登录日志表),再问一个问题(比如 当天的DAU是多少), chatglm会给出错误的sql语句。 比如加了一些无关的字段、sql关键字之间没有空格、用户没有去重等
期望通过微调,提升模型的text2sql能力。
期望注入:
问题:
输出:
select count(distinct yourid) from your_table where date = today()
从your_table表查询XX的DAU, 以yourid字段作为用户的唯一标识,以date字段作为过滤时间。通过count(distinct yourid)进行去重统计,date=today() 指定为今天。
The text was updated successfully, but these errors were encountered: