| --- |
| 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/junyeong-nero/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 |
|
|
