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-00006-of-00014.bin
- Xet hash:
- 6f94cba994097576809e75f88cbbe07d1cdac9460950b30b06e9e51e73d3522a
- Size of remote file:
- 4.88 GB
- SHA256:
- a63f21d31cc1fbe26f2fd54c7b154f27ffd2e8580136fb405fe903451cf2b582
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