| license: mit | |
| tags: | |
| - tiny-stable-diffusion | |
| - diffusion | |
| - image-generation | |
| - diffusion | |
| library_name: pytorch | |
| # tiny-sd-models | |
| This is a **DIFFUSION** model trained with [tiny-stable-diffusion](https://github.com/your-username/tiny-stable-diffusion). | |
| ## Model Description | |
| This is a Diffusion Transformer (DiT/MMDiT) trained for text-to-image generation in latent space. | |
| ### Architecture | |
| - **Type**: DiT or MMDiT (Multi-Modal Diffusion Transformer) | |
| - **Conditioning**: CLIP text embeddings | |
| ## Usage | |
| ```python | |
| import torch | |
| from src.models.vae import create_vae # or appropriate model import | |
| # Load checkpoint | |
| checkpoint = torch.load("model.pt", map_location="cpu") | |
| # Create model and load weights | |
| model = create_model(...) # Use config from checkpoint | |
| model.load_state_dict(checkpoint["model_state_dict"]) | |
| ``` | |
| ## License | |
| MIT License | |