Shypd.aiThe largest open index of AI toolsTunix is a JAX-based library designed to streamline the post-training of Large Language Models (LLMs). It provides efficient and scalable support for supervised fine-tuning, reinforcement learning, and agentic RL on TPUs.
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Tunix (Tune-in-JAX) is a JAX-based library developed by Google, specifically engineered to optimize the post-training phase of Large Language Models (LLMs). It offers efficient and scalable support for various advanced training methodologies, including Supervised Fine-Tuning (SFT), Reinforcement Learning (RL), and Agentic RL. Leveraging the power of JAX, Tunix ensures accelerated computation and seamless integration with JAX-based modeling frameworks like Flax NNX. It also integrates with high-performance inference engines such as vLLM and SGLang-JAX for efficient rollout. Tunix is designed to work within the JAX training stack, utilizing foundational tools like Flax and Optax, and streamlining tuning workflows on XLA and JAX infrastructure. It supports a growing list of models including Gemma, Llama, and Qwen families.
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