Tinker is a newly launched API designed for fine-tuning language models, allowing researchers to easily customize and experiment with various models without managing the underlying infrastructure. The service supports both large and small models and is currently in private beta, with plans for onboarding users and introducing usage-based pricing soon.

The article discusses the intricacies of fine-tuning APIs, highlighting the importance of understanding their structure and functionality for better integration in applications. It emphasizes best practices and strategies for optimizing API performance and adapting them to specific user needs.

Tinker is a flexible training API designed for researchers and developers, allowing them to fine-tune open-source models efficiently using LoRA technology. It manages infrastructure while providing control over training processes, enabling users to focus on their data and algorithms. Tinker supports various model sizes and will soon introduce usage-based pricing after an initial free period.