Instructions to use WaveCut/Cosmos3-Super-Text2Image-SDNQ-Int8-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-Int8-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-Int8-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

- Xet hash:
- a8fa9f99f5912169dbeb06b9ad0eabc31255a8202403bd4934415871ddb317fe
- Size of remote file:
- 1.24 MB
- SHA256:
- 215e5917348588a657ef6c2d55a52392dbed666f02f7d3ed6fb3e775bf9d94cb
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