Learn how to build a Text-to-Image application using DALL-E mini in Python from scratch in this comprehensive 40-minute AI workshop. Follow step-by-step instructions to download pre-built model files, set up a Python runtime environment, and process text input to generate target images using GPU capabilities. Explore the fundamentals of text-to-image AI research, solution design, and component selection. Dive into practical coding sessions, including package installation, model instantiation, and tokenizer loading. Master key functions such as inference and decoding, and learn to set input prompts and model parameters. Overcome common errors and test the application with various inputs. Access GitHub resources for further exploration and development of your text-to-image AI skills.
AI Workshop - Build Your Own Text-to-Image Application with DALL-E Mini in Python from Scratch
Overview
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
Taught by
Prodramp
