Instructions to use cuio/URSA-0.6B-FSQ320 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuio/URSA-0.6B-FSQ320 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cuio/URSA-0.6B-FSQ320", 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
| { | |
| "_class_name": "URSAPipeline", | |
| "tokenizer": [ | |
| "transformers", | |
| "Qwen2TokenizerFast" | |
| ], | |
| "scheduler": [ | |
| "__scheduler__", | |
| "KineticOptimalScheduler" | |
| ], | |
| "transformer": [ | |
| "__transformer__", | |
| "URSATransformer3DModel" | |
| ], | |
| "vae": [ | |
| "__vae__", | |
| "AutoencoderVQCosmos3D" | |
| ] | |
| } | |