TIPO-100M
| Property | Value |
|---|---|
| Parameter Count | 100M |
| Architecture | LLaMA |
| License | Apache-2.0 |
| Training Data | Danbooru2023, LAION, COYO-HD-11M, GBC10M |
| Language | English |
What is TIPO-100M?
TIPO-100M is an innovative text-to-image prompt optimization model that leverages the LLaMA architecture to enhance the quality of text-to-image generation. It's designed to perform "Text Presampling" within the inference pipeline, helping to refine and extend user input prompts for better image generation results.
Implementation Details
Built on the LLaMA architecture, TIPO-100M is trained on a diverse set of datasets including Danbooru2023, LAION Conceptual Captions, COYO-HD-11M, and GBC10M. The model operates with a maximum context length of 1024 tokens and uses F32 tensor type for computations.
- Specialized prompt optimization for text-to-image systems
- Integration with popular stable diffusion interfaces
- Comprehensive training on multiple image-text paired datasets
Core Capabilities
- Prompt refinement and extension
- Enhanced text-to-image generation quality
- Seamless integration with existing T2I pipelines
- Support for various stable diffusion interfaces including webui and ComfyUI
Frequently Asked Questions
Q: What makes this model unique?
TIPO-100M is specifically designed for prompt optimization in text-to-image generation, using a unique text presampling approach that improves output quality with minimal user effort.
Q: What are the recommended use cases?
The model is ideal for enhancing text-to-image generation workflows, particularly when using stable diffusion models. It's especially useful for users who want to improve their prompt engineering without deep expertise.
