G3D-ViT is a 3D GradCAM implementation for Vision Transformers (ViTs), designed to visualize important regions in 3D data by leveraging gradient-based activation maps. This method is particularly ...
Train large language models across multiple GPUs using Tensor Parallelism, Data Parallelism (FSDP), and Context Parallelism — all with native PyTorch and HuggingFace Transformers. This workflow trains ...
Abstract: Recently, diffusion Transformers have demonstrated strong potential in generative tasks, especially in 2D image generation, where DiT models have shown excellent generative results. The ...
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