Instructions to use WaveCut/Cosmos3-Super-Text2Image-SDNQ-Uint4-SVD-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Cosmos3-Super-Text2Image-SDNQ-Uint4-SVD-Transformer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Cosmos3-Super-Text2Image-SDNQ-Uint4-SVD-Transformer", torch_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
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 132 Bytes
69ded5e | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:ed588aaca0a388e794594b72ed30f551e27fc37d31000f76e29fd2593c9a8212
size 1258197
|