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In practice, CodeT5 and CodeT5+ models can be deployed as an AI-powered coding assistant to boost the productivity of software developers. At Salesforce, we build an AI coding assistant demo using CodeT5 as a VS Code plugin to provide three capabilities: Text-to-code generation: generate code based on the natural language description.
CodeT5 achieves state-of-the-art performance on multiple code-related downstream tasks including understanding tasks such as code defect detection and clone detection, and generation tasks across various directions including PL-NL, NL-PL, and PL-PL. In what follows, we will explain how CodeT5 works.
CodeT5 (base-sized model) Pre-trained CodeT5 model. It was introduced in the paper CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation by Yue Wang, Weishi Wang, Shafiq Joty, Steven C.H. Hoi and first released in this repository.
TL;DR: CodeT5+ is a new family of open code large language models (LLMs) with improved model architectures and training techniques. CodeT5+ achieves the state-of-the-art performance among the open-source LLMs on many challenging code intelligence tasks, including zero-shot evaluation on the code generation benchmark HumanEval.
CodeT5 is a new model that uses Transformer technology for better code understanding and generation. It is based on the T5 architecture, which has been extended to include two identifier tagging and prediction tasks that help the model to better leverage the token type information from programming languages.
Sep 2, 2021 · We present CodeT5, a unified pre-trained encoder-decoder Transformer model that better leverages the code semantics conveyed from the developer-assigned identifiers. Our model employs a unified framework to seamlessly support both code understanding and generation tasks and allows for multi-task learning.
Oct 25, 2021 · This is the official PyTorch implementation for the following EMNLP 2021 paper from Salesforce Research: Title: CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation. Authors: Yue Wang, Weishi Wang , Shafiq Joty, and Steven C.H. Hoi.
CodeT5 is a Transformer-based model for code understanding and generation based on the T5 architecture. It utilizes an identifier-aware pre-training objective that considers the crucial token type information (identifiers) from code.
Official research release for CodeT5 and CodeT5+ models for Code Understanding and Generation from Salesforce Research, which are introduced by the following papers: Title: CodeT5+: Open Code Large Language Models for Code Understanding and Generation.
4 days ago · Abstract. Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently shown to transfer well to Programming Languages (PL) and largely benefit a broad set of code-related tasks.
