Enhance your LLMs’ coding capabilities with human-generated training and evaluation datasets for improved code generation, debugging, and test case creation.
Turing combines advanced AI technology with human expertise to train LLMs for coding excellence. Our team of professionals designs and evaluates datasets to improve code generation, error resolution, and adherence to best development practices. Leverage our expertise to ensure your LLMs deliver precise, secure, and efficient coding outputs tailored to your needs.
Our experts work with you to define your coding requirements, evaluate current gaps, and set clear training objectives tailored to your business needs.
We assemble a team of coding experts and data scientists to design high-quality, language-specific datasets. Use a human-in-the-loop approach to ensure accuracy, relevance, and task-specific coverage.
Train and fine-tune your LLMs with advanced techniques, focusing on secure, efficient, and task-oriented coding capabilities. Incorporate real-world debugging scenarios and edge-case handling.
Expand your AI’s coding expertise as your business grows. Scale training efforts to integrate new languages, frameworks, or domain-specific requirements seamlessly.
Talk to our solutions architects and explore how Turing’s coding training solutions can transform your AI-powered software development.
Empower your research teams without sacrificing your budget or business goals. Get our starter guide on strategic use, development of minimum viable models, and prompt engineering for a variety of applications.
“Turing’s ability to rapidly scale up global technical talent to help produce the training data for our LLMs has been impressive. Their operational expertise allowed us to see consistent model improvement, even with all of the bespoke data collection needs we have.”
Talk to our solutions architects and explore how Turing’s coding training solutions can transform your AI-powered software development.
LLMs can perform code generation, completion, debugging, inline suggestions, test case creation, and competitive programming solutions.
Our team of coding experts designs datasets tailored to specific languages and tasks, validated through a human-in-the-loop process for accuracy and relevance.
Yes, we train models to identify vulnerabilities, handle adversarial prompts, and produce sanitized, secure code to prevent security risks.
We train models on annotated datasets of common errors, including step-by-step solutions, to improve error resolution and debugging capabilities.
We specialize in Python, Java, C++, SQL, Verilog, Haskell, and more, ensuring your models excel across multiple languages.
Yes, we use RAG methods to incorporate internal repositories, coding styles, and best practices into the models for real-time, context-aware support.
Synthetic data covers edge cases and complex scenarios, ensuring models are robust, adaptable, and capable of handling diverse coding tasks.