One of the most recent developments in natural language processing (NLP) is the emergence of large-scale linguistic models (LLMs) built using vast datasets. There are several LLMs, such as Google’s BERT and OpenAI’s GPT-2 and GPT-3. With these models, it is possible to generate everything from simple essays to accurate financial models.
including AI startup Open AI, Hug face, Correlation, AI21 Labs are pushing the boundaries of LLM by training models with billions of parameters.
Here are five AI-based code generators based on big language models that can generate high-quality code:
1. Open AI Codex
Open the AI Codex It is a model based on GPT-3 GitHub Assistant Pilot It’s a tool from GitHub for creating code in major development environments, including VS Code, NeoVim, JetBrains, and even in the cloud. GitHub Codespaces. He claims to write code in at least a dozen languages, including JavaScript, Go, Perl, PHP, Ruby, Swift and TypeScript, as well as BASH. The model is trained on billions of lines of code available in public domain such as GitHub repositories.
OpenAI has made the model available through a private beta for developers and platform companies to build tools and integrations.
2. Tabnin
While Tabnin It’s not an end-to-end code generator, it puts the auto-completion feature of an integrated development environment (IDE) on steroids. Built in Rust by Jacob Jackson when he was a student at the University of Waterloo, Tabnin has evolved into a fully-fledged AI-based code completion tool.
Tabnin supports more than 20 languages and 15 editors, including popular IDEs like VS Code, IntelliJ, Android Studio, and Vim. Available for a team of 3 developers for $432 per year.
3. CodeT5
CodeT5 It is an open source programming language model developed by SalesForce researchers. It is based on the Google T5 (Text to Text Transformer) framework. To train CodeT5, the team obtained more than 8.35 million code instances from publicly accessible GitHub repositories, including user comments. Most of these datasets come from the CodeSearchNet dataset, including Ruby, JavaScript, Go, Python, PHP, C, and C#, in addition to BigQuery’s two C and C# datasets.
CodeT5 can bring three capabilities to software programming:
- From text to code generationCode generation based on natural language description
- Code auto-completionComplete the entire function of the code given the name of the target function
- Code summaryGenerate a summary of a function in a natural language description
4. Polycoder
Polycoder It is an open source alternative to OpenAI’s Codex. Developed by researchers at Carnegie Mellon University, the model is based on OpenAI’s GPT-2 and is trained on a 249 GB code base in 12 programming languages. According to the developers of Polycoder, the program can write C with greater accuracy than any other model, including codecs.
While most code generators are not open source, Polycoder is one of the first open source code generation models.
5. Program
Program, Y-Combinator, a Berlin-based startup, is a code generation tool aimed at data scientists and Python programmers using SQL queries and Jupyter notebooks. Data scientists can write English-language queries that the tool translates into complex SQL queries by joining and grouping them. It supports SQLite, PostgreSQL, MySQL and Amazon Redshift.
Python and Julia developers can integrate Cogram with Jupyter Notebooks to automate code generation. The tool can generate context code for a specific task based on the feedback. Data scientists can create visualizations based on major Python modules such as Matplotlib, Plotly, or Seaborn.
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