The Loongforge open-source framework significantly accelerates the training of embodied models

Automated excerpt

Anyone involved in model training can likely relate to these challenges: the number of tasks keeps growing, experiment queues are getting longer, and computing bills are becoming increasingly terrifying. Today, I’d like to share our recent open-source project: https://github.com/baidu-baige/LoongForge. What we are doing is simple: accelerating training speed while keeping the output exactly the same. Currently, the LoongForge acceleration framework covers a batch of mainstream embodied AI models (such as pi05, GR00T, xVLA, FastWAM, Lingbot-VA, Cosmos, Dreamzero, Wall-oss-0.5, etc.). Below is a demonstration using DreamZero (an embodied AI model).

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