AI Workshop - Build Your Own Text-to-Image Application with DALL-E Mini in Python from Scratch

This workshop guides learners through building a Python text-to-image application with pre-trained DALL-E mini and VQGAN models. It covers model setup, tokenization, inference, decoding, parameter configuration, troubleshooting, and generating images from prompts.

Syllabus

- Content Intro
- Why Text-to-image AI Research?
- Previous reference videos
- Solution Design and components
- Finalizing Models for the solution
- DALL-e mini model resources
- Components and Model Finalization
- Coding at Colab Starts
- Package Installation
- Downloading all files to local folder
- Instantiate DALL-e mini main model
- Instantiate VQGAN Model
- Loading Tokenizer to create text processor
- Creating Inference function
- Creating Decode Function
- Setting Text Input Prompt
- Defining Model Parameters
- Processing Text and Generating Results
- Hitting known error and by passing it
- Text to Image Results
- Re-testing app with different input
- Workshop Code at GitHub
- Conclusion