TRL is a cutting-edge library designed for post-training foundation models using advanced techniques like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), and Direct Preference Optimization (DPO). Built on top of the 🤗 Transformers ecosystem, TRL supports. Use it to navigate the topic and choose relevant methods, papers or tools.
Implementation of Band Split Roformer , SOTA Attention network for music source separation out of ByteDance AI Labs. They beat the previous first place by a large margin.
Implementation of SoundStorm , Efficient Parallel Audio Generation from Google Deepmind, in Pytorch. They basically applied MaskGiT to the residual vector quantized codes from Soundstream .
As of February 10th, 2025, this repository is read-only. Please visit github.com/NVIDIA/Cosmos for the latest updates and support on Cosmos Tokenizer.
TRL is a cutting-edge library designed for post-training foundation models using advanced techniques like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), and Direct Preference Optimization (DPO). Built on top of the 🤗 Transformers ecosystem, TRL supports. Use it to navigate the topic and choose relevant methods, papers or tools.
Implementation of Band Split Roformer , SOTA Attention network for music source separation out of ByteDance AI Labs. They beat the previous first place by a large margin.
Implementation of SoundStorm , Efficient Parallel Audio Generation from Google Deepmind, in Pytorch. They basically applied MaskGiT to the residual vector quantized codes from Soundstream .
As of February 10th, 2025, this repository is read-only. Please visit github.com/NVIDIA/Cosmos for the latest updates and support on Cosmos Tokenizer.