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 / examples /06_robotic_assembly_line_signage_modelopt_fp8.png

- Xet hash:
- 2b8d4e78224ce85b6bf425aa0471ff1ced0667ea5207fb803b93b5e53b716024
- Size of remote file:
- 1.48 MB
- SHA256:
- aa47e70e8b0ad1fad84e0b5d9b96da386de2ac342a573e6469908541c65b2f70
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