Stable Code 3B: Transforming the Coding Landscape with AI

he arrival of AI in the world of software development represents a groundbreaking transformation, and the most recent advancement in this journey is the unveiling of Stable Code 3B. This generative AI-powered code generation is becoming increasingly potent and compact. Stable Code 3B, boasting an impressive 3 billion parameters, is set to revolutionize the coding landscape by concentrating on code completion capabilities for software development. What’s remarkable is that despite its reduced size, Stable Code 3B maintains a similar high-level performance across various programming languages.

Reshaping coding

This revolutionary AI tool promises to reshape the coding landscape, offering unparalleled efficiency, precision, and innovation. So, let’s delve into what Stable Code 3B entails and how it’s reshaping our approach to programming.

Flexibility of stable code 3B

Designed primarily for precise and responsive code completion, Stable Code 3B manages to outshine models twice its size, such as CodeLLaMA 7B. Its compact dimensions empower it to operate seamlessly on modern laptops devoid of dedicated GPUs. It has been trained on a comprehensive spectrum of 18 programming languages, delivering state-of-the-art performance when compared to similarly-sized models. The introduction of Stable Code 3B not only involves the model suggesting new lines of code but also filling in substantial gaps within existing code, a remarkable capability known as Fill in the Middle (FIM). This powerful feature is now accessible through the Stability AI Membership for commercial applications.

Rotary Position Embeddings (RoPE) technique

Moreover, the model’s training has been fine-tuned with an expanded context size, employing the innovative Rotary Position Embeddings (RoPE) technique, which optionally allows for a context length of up to 100k tokens. RoPE is a technique also utilized by other large language models, including Meta’s Llama 2 Long. Stable Code 3B builds upon Stability AI’s Stable LM 3B natural language model, with additional training that hones its code completion capabilities while preserving its prowess in general language tasks.

Code 3B Model

The model’s training data encompassed code repositories, programmer forums, and various technical sources, covering widely-used languages such as Python, Java, JavaScript, Go, Ruby, and C++. Initial benchmarks indicate that it not only matches but often surpasses the completion quality of models twice its size.

The generative AI code generation tools market is fiercely competitive, with options like Meta’s CodeLLaMA 7B and the 3-billion parameter StarCoder LLM, developed in collaboration with IBM, HuggingFace, and ServiceNow, gaining popularity. In this arena, Stability AI proudly asserts that Stable Code 3B outperforms StarCoder across a range of programming languages, including Python, C++, JavaScript, Java, PHP, and Rust.

Stable Code 3B features

Stable Code 3B goes a step further by offering an array of features and significantly improved performance across multiple languages. It introduces benefits like support for Fill in the Middle capabilities (FIM) and an expanded context size. While the base Stable Code is trained on sequences of up to 16,384 tokens, it follows a similar approach to CodeLlama by implementing Rotary Embeddings, optionally allowing for modification of the rotary base, extending the model’s context length to up to 100k tokens.

Subscription to Stable Code 3B

Stable Code 3B is now available for commercial use as part of Stability AI’s new membership subscription service, first unveiled in December. As part of this subscription offering, members gain access to Stable Code 3B, along with a suite of other AI tools in Stability AI’s portfolio, including the SDXL stable diffusion image generation tools, StableLM Zephyr 3B for text content generation, Stable Audio for audio generation, and Stable Video for video generation.