Shap-E            Shap-E is a conditional model for generating 3D assets which could be used for video game development, interior design, and architecture. It is trained on a large dataset of 3D assets, and post-processed to render more views of each object and produce 16K instead of 4K point clouds. The Shap-E model is trained in two steps: an encoder accepts the point clouds and rendered views of a 3D asset and outputs the parameters of implicit functions that represent the asset a diffusion model is trained on the latents produced by the encoder to generate either neural radiance fields (NeRFs) or a textured 3D mesh, making it easier to render and use the 3D asset in downstream applications This guide will show you how to use Shap-E to start generating your own 3D assets! Before you begin, make sure you have the following libraries installed:   Copied # uncomment to install the necessary libraries in Colab