The Salesforce team has created and open-sourced a new identifier-aware unified pre-trained encoder-decoder model called CodeT5 . So far, they have demonstrated state-of-the-art results in multiple code-related downstream tasks such as understanding and generation across various directions, including PL to NL, NL to PL, and from one programming language to another.
CodeT5 is built on a similar architecture to Google’s T5 framework. It reframes text-to-text, where the input and output data are always strings of texts. This allows any task to be applied by this uninformed model.
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current coding pre-training systems heavily rely on either an encoder-only model similar to BERT or a decoder-only model like GPT.
Either way, it is suboptimal for generation and understanding tasks.
CodeBERT needs an additional decoder when used for tasks like code summarization. Apa...
The research team of CodeT5 had over 8.35 million examples to train the AI on, including user-written comments from open source GitHub repositories. While training, the largest and most capable version of CodeT5, which had 220 million parameters, took 12 days on a cluster of 16 Nvidia A100 GPUs 4...
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