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
Cosmos3-Super-Text2Image-SDNQ-Int8-Transformer / examples /03_control_room_restoration_sdnq_int8.png
Download examples/03_control_room_restoration_sdnq_int8.png from WaveCut/Cosmos3-Super-Text2Image-SDNQ-Int8-Transformer: direct link, hf CLI and curl.
- Browser
- Download file 1.52 MB
-
https://huggingface.co/WaveCut/Cosmos3-Super-Text2Image-SDNQ-Int8-Transformer/resolve/main/examples/03_control_room_restoration_sdnq_int8.png
- Command line
-
hf download hf://WaveCut/Cosmos3-Super-Text2Image-SDNQ-Int8-Transformer/examples/03_control_room_restoration_sdnq_int8.png
-
curl -L -o 03_control_room_restoration_sdnq_int8.png https://huggingface.co/WaveCut/Cosmos3-Super-Text2Image-SDNQ-Int8-Transformer/resolve/main/examples/03_control_room_restoration_sdnq_int8.png
1.52 MB

- Xet hash:
- 737a5b15061186dc63540b6c221154e21f4c0e92b162fa9b7d8d346781bac7e4
- Size of remote file:
- 1.52 MB
- SHA256:
- 9ccf076a500ebb5bb2d2d2114daa7de6041b812e8f26799c73695fed054e3ec2
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