SQL (Structured Query Language) conversion method and system based on language model coding and multi-task decoding
A technology of language model and conversion method, which is applied in the direction of neural learning method, biological neural network model, special data processing application, etc., can solve the problems of unable to meet the joint coding requirements of text and database mode, poor scalability, complex model design, etc., to achieve Strong feature encoding ability and generalization, improve accuracy, and alleviate the effect of lack of labeled data
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[0031] The present invention will be further elaborated and illustrated below in conjunction with the accompanying drawings and specific embodiments.
[0032] Such as figure 1 Shown, a kind of SQL conversion method based on language model coding and multi-task decoding, comprises the following steps:
[0033] 1. According to the type of the query database, the language model encoder is pre-trained. The language model encoder includes an Embedding layer and a Transformer network, and the pre-trained language model encoder is obtained after training;
[0034] 2. Expand the query database in turn according to the table name and column name, convert the two-dimensional table into a one-dimensional text sequence, combine the user query statement to form the input sequence X, and give the target SQL sequence corresponding to the user query statement;
[0035] 3. Use the sequence X as the input of the Embedding layer of the pre-trained language model encoder to obtain the initial en...
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