Cosmos
Diffusers
Safetensors
cosmos3_omni
nvidia
cosmos3
vllm
vllm-omni
text, image, video, audio, and action generation
omnimodel
Instructions to use nvidia/Cosmos3-Nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use nvidia/Cosmos3-Nano 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-Nano 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-Nano", 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
Add any-to-any pipeline tag, update library metadata and link paper
#16
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team.
I've opened this PR to improve the model card metadata and content. Specifically:
- Added the
any-to-anypipeline tag to correctly categorize this omnimodal model. - Updated the
library_nametodiffusersas there is clear evidence of integration in the repository and usage examples. - Linked the model to its research paper on Hugging Face.
- Included a sample usage section for
diffusersbased on the official documentation.