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
- Draw Things
- DiffusionBee
Cosmos3-Super-Text2Image-ModelOpt-FP8-Transformer / examples /07_kitchen_storm_chess_table_modelopt_fp8.png

- Xet hash:
- f8cb9e72434dfd2e993813b3462624f5e6a4a37bad3f138390d4d4f4f3d8d7d3
- Size of remote file:
- 1.48 MB
- SHA256:
- 086b103890d9256d1c8443f9842933b69dd40a5e9d86ecdd693cb4eb1ce906ef
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