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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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Problem Statement
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...
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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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