Cosmos
Diffusers
Safetensors
cosmos3_omni
nvidia
cosmos3
vllm
vllm-omni
sglang
sglang-diffusion
text, image, video, audio, and action generation
omnimodel
Instructions to use nvidia/Cosmos3-Nano-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use nvidia/Cosmos3-Nano-FP8 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-FP8 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-FP8", 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/example_t2v_output.mp4 from nvidia/Cosmos3-Nano-FP8: direct link, hf CLI and curl.
- Browser
- Download file 8.58 MB
-
https://huggingface.co/nvidia/Cosmos3-Nano-FP8/resolve/main/assets/example_t2v_output.mp4
- Command line
-
hf download hf://nvidia/Cosmos3-Nano-FP8/assets/example_t2v_output.mp4
-
curl -L -o example_t2v_output.mp4 https://huggingface.co/nvidia/Cosmos3-Nano-FP8/resolve/main/assets/example_t2v_output.mp4
8.58 MB
- Xet hash:
- b0bddc1570fd9969a2ba719b6bde03a4671db5ffae63fa11cf8d82a5beadfefd
- Size of remote file:
- 8.58 MB
- SHA256:
- 43b5d40b586441efb15d0acab140f1bf54e553bb73cbf33c0d07ac40ce4b0fc4
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