Pytorch 加载 模型

Implementation of SoundStorm, Efficient Parallel Audio Generation from Google Deepmind, in Pytorch

My pytorch environments

Implementation of 🦩 Flamingo, state-of-the-art few-shot visual question answering attention net out of Deepmind, in Pytorch

Implementation of Natural Speech 2, Zero-shot Speech and Singing Synthesizer, in Pytorch

A well-packed PyTorch development runtime, CUDA ready.

Implementation of the training framework proposed in Self-Rewarding Language Model, from MetaAI

pytorch-cuda development

在做深度学习项目时，从头训练一个模型是需要大量时间和算力的，我们通常采用加载预训练权重的方法，而我们往往面临以下几种情况： 未修改网络，A与B一致 很简单，直接.load_state_dict() net=ANet(num_classses=5,init_weights=True)net.to(de