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 / transformer /diffusion_pytorch_model-00001-of-00014.bin
- Xet hash:
- c15831ff1f1b7c726cee4721b608433b5207e4b1fb2cb1ccc447e39ecf3e4dad
- Size of remote file:
- 4.93 GB
- SHA256:
- b6e3b47a834bef64dc72502f59a5099941fb61aeade649696a0428a2f24fe982
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