DALL-E Mini Explained - ML Coding Series

Dive into a comprehensive video tutorial exploring the DALL-E mini project, an open-source implementation of DALL-E. Begin with an overview of essential concepts including VQ-GAN, BART, GLU, and DALL-E papers. Examine the Weights & Biases report on DALL-E mini before delving into the actual code. Learn about text tokenization, BART encoder and decoder, GLU (Gated Linear Units), image latent vector autoregressive generation, super conditioning, top-k sampling, and VQGAN decoder. Gain insights into the inner workings of AI-powered image generation models through this in-depth exploration of min(DALL-E), the minimal PyTorch port of DALL-E mini.

Intro
VQGAN overview
Conditioning in VQGAN
BART transformer
DALL-E 1 overview
DALL-E mini Weights & Biases report
[code] min-dalle
Text tokenizer
BART encoder
GLU explained paper + code
BART decoder
Image latent vector autoregressive generation
Super conditioning, top-k sampling
VQGAN decoder
Outro