Instructions to use WaveCut/Cosmos3-Super-Text2Image-ModelOpt-FP8-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Cosmos3-Super-Text2Image-ModelOpt-FP8-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-ModelOpt-FP8-Transformer", 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
Cosmos3-Super-Text2Image-ModelOpt-FP8-Transformer / examples /03_control_room_restoration_modelopt_fp8.png

- Xet hash:
- 24f17385f043664fa05312da7f11e861b08c5ff1b6e413a4298a67bdf07a8867
- Size of remote file:
- 1.53 MB
- SHA256:
- 7827fed553972dbf6e6bd38398bb1c59fda2f4fdb42aeb02197aa35a621596b4
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