TIPO-500M
| Property | Value |
|---|---|
| Parameter Count | 508M |
| Architecture | LLaMA |
| Training Datasets | Danbooru2023, Coyo-HD-11M, GBC10M |
| License | Kohaku License 1.0 |
| Training Hardware | H100 x 8 |
| Context Length | 1024 tokens |
What is TIPO-500M?
TIPO-500M is an advanced text-to-image prompt optimization model that leverages the LLaMA architecture to enhance the quality of image generation prompts. The model represents a significant advancement in Text-to-Image (T2I) generative modeling, trained on approximately 30B tokens across multiple high-quality datasets.
Implementation Details
Built on the LLaMA architecture, TIPO-500M was trained using 8 H100 GPUs over 100 hours. The model implements text presampling within the inference pipeline, utilizing a context length of 1024 tokens and a batch size of 3584 during training.
- Trained on multiple datasets including Danbooru2023, GBC10M, and Coyo-HD-11M
- Utilizes advanced text presampling techniques
- Implements efficient prompt optimization strategies
- Supports integration with major stable diffusion interfaces
Core Capabilities
- Enhanced prompt generation for improved image output
- Superior aesthetic scores compared to baseline models
- Effective handling of both short and truncated long prompts
- Seamless integration with existing T2I pipelines
Frequently Asked Questions
Q: What makes this model unique?
TIPO-500M stands out through its specialized text presampling approach, which enables superior prompt optimization for text-to-image generation. The model has demonstrated improved performance in both FDD scores and aesthetic metrics compared to conventional approaches.
Q: What are the recommended use cases?
The model is particularly effective for enhancing user prompts in text-to-image generation systems, especially when working with stable-diffusion-webui, stable-diffusion-webui-forge, and ComfyUI. It excels in both scenario-based generation and handling various prompt lengths.
