Instructions to use WaveCut/Cosmos3-Super-Text2Image-ModelOpt-NVFP4-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-NVFP4-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-NVFP4-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
- Draw Things
- DiffusionBee
Cosmos3-Super-Text2Image-ModelOpt-NVFP4-Transformer / examples /09_flood_command_center_modelopt_nvfp4.png

- Xet hash:
- 11d316e128f7d588eab336b5f0b929069c93c6c1007be1bd0a994c52ed815981
- Size of remote file:
- 1.65 MB
- SHA256:
- b34e8b132c17099f20a57f70024052208b4e0784ea7e0e29ba53899ff07fbda2
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