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Unlock the full potential of your large language models with Tunix, an innovative open-source JAX-based library for post-training. This video explains the two-stage LLM training process, focusing on how Tunix excels in the post-training phase to instill strong reasoning capabilities. See a practical example of using Tunix with reinforcement learning to improve math problem-solving, leveraging its efficiency on accelerators like Google TPUs. Improve your LLM performance with this powerful tool.
Chapters:
0:00 – Introduction to Tunix
0:17 – Understanding LLM training stages
0:35 – Tunix: A JAX-based LLM post-training library
0:50 – Exploring Tunix’s capabilities and supported models
1:05 – Reinforcement learning for LLMs overview
1:25 – RLVR for math reasoning demo (GSM8K dataset)
1:50 – Setting up and training with GRPO
2:05 – Tunix performance results and benefits
2:20 – Getting involved with Tunix
Speaker: Wei Wei
Products Mentioned: Google AI Read More Google for Developers
