Best AI Coding Assistants for Java

Codey accelerates the software development process with real-time code generation and completion, customized to a client's codebase. This code generation model is compatible with 20+ coding language, including Go, Google Standard SQL (GSS), Java, Javascript and Python. It allows developers to perform a wide range of coding tasks. This helps them work faster and close skill gaps by: Code completion: Codey suggests a few lines of code based on context. Code generation: Codey creates code using natural language prompts provided by a developer. Code chat: Codey allows developers to converse with a robot for help with debugging and documentation, learning new concepts and other code-related issues.

StableCode is a unique tool that helps developers become more efficient in their coding by using three models. The base model was trained first on a diverse collection of programming languages using the stack-dataset from BigCode, and then further trained with popular languages such as Python, Go, Java, Javascript, C, markdown and C++. We trained our models using 560B tokens on our HPC Cluster. After the base model was established, the instruction models were tuned for specific usecases to help solve complex programming problems. To achieve this result, 120,000 code instructions/response pair in Alpaca format was trained on the base. StableCode is a great tool for anyone who wants to learn more about programming. The long-context model is a great assistant for ensuring that autocomplete suggestions for single- and multiple-line input are available to the user. This model was designed to handle a large amount of code at once.

CodeGemma consists of powerful lightweight models that are capable of performing a variety coding tasks, including fill-in the middle code completion, code creation, natural language understanding and mathematical reasoning. CodeGemma offers 3 variants: a 7B model that is pre-trained to perform code completion, code generation, and natural language-to code chat. A 7B model that is instruction-tuned for instruction following and natural language-to code chat. You can complete lines, functions, or even entire blocks of code whether you are working locally or with Google Cloud resources. CodeGemma models are trained on 500 billion tokens primarily of English language data taken from web documents, mathematics and code. They generate code that is not only syntactically accurate but also semantically meaningful. This reduces errors and debugging times.