Instructions to use wfen/Cosmos3-Nano-FP8-Blockwise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wfen/Cosmos3-Nano-FP8-Blockwise with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wfen/Cosmos3-Nano-FP8-Blockwise", 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
- Xet hash:
- f678d02a33c7e8ba3929314bcc014082001a8f65cc2ab5ac3c9375f09883d847
- Size of remote file:
- 235 Bytes
- SHA256:
- 59f66244bab8c69e7a2afcb45b59216b4239b15acc58a83036056fededccac3f
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