Instructions to use CSWRY/VOSR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CSWRY/VOSR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CSWRY/VOSR", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| { | |
| "resolution": 512, | |
| "patch_size": 2, | |
| "mlp_ratio": 4, | |
| "use_qknorm": true, | |
| "use_swiglu": true, | |
| "use_rope": true, | |
| "use_rmsnorm": true, | |
| "wo_shift": false, | |
| "dim": 1024, | |
| "depth": 28, | |
| "num_heads": 16, | |
| "ae_type": "sd2", | |
| "ae_path": "preset/ckpts/stable-diffusion-2-1-base", | |
| "time_dist": ["uniform", 0, 1.0], | |
| "cfg_ratio": 0.1, | |
| "cfg_scale": 0.5, | |
| "dinov2_size": 448, | |
| "enc_type": "dinov2b", | |
| "enc_dim": 768, | |
| "layer_dinov2b_list": [8], | |
| "interp_type": "lin", | |
| "encdim_ratio": 3, | |
| "weak_cond_strength_aelq_list": [0.05, 0.25], | |
| "weak_cond_strength_aelq": 0.1, | |
| "cond_strength_aelq_list": [5, 1], | |
| "t_start": 0, | |
| "t_end": 1, | |
| "distill_type": "rcgm" | |
| } | |