Text-to-Image
Cosmos
Diffusers
Safetensors
cosmos3_omni
nvidia
cosmos3
vllm-omni
sglang
sglang-diffusion
image-generation
Instructions to use nvidia/Cosmos3-Super-Text2Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use nvidia/Cosmos3-Super-Text2Image with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Diffusers
How to use nvidia/Cosmos3-Super-Text2Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nvidia/Cosmos3-Super-Text2Image", 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
Download assets/benchmark-text2image.png from nvidia/Cosmos3-Super-Text2Image: direct link, hf CLI and curl.
- Browser
- Download file 147 kB
-
https://huggingface.co/nvidia/Cosmos3-Super-Text2Image/resolve/main/assets/benchmark-text2image.png
- Command line
-
hf download hf://nvidia/Cosmos3-Super-Text2Image/assets/benchmark-text2image.png
-
curl -L -o benchmark-text2image.png https://huggingface.co/nvidia/Cosmos3-Super-Text2Image/resolve/main/assets/benchmark-text2image.png
147 kB

- Xet hash:
- 1c8681664623aa229a89595ac0fb7f6d265a5e2dccc04f76c8c447784e862c13
- Size of remote file:
- 147 kB
- SHA256:
- 55bdd6bc617832086be44c3d63f03cb28426dc352a97e8d3c10ae7967b94c4e9
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