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-Super with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use nvidia/Cosmos3-Super 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 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", 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
Update MC
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by kediwu0331 - opened
README.md
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Cosmos 3 support in SGLang Diffusion currently requires the SGLang main branch. Switch to a stable SGLang release once Cosmos 3 support is included there.
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```bash
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sglang serve \
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--model-path nvidia/Cosmos3-Super
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--num-gpus 4
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```
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Cosmos 3 support in SGLang Diffusion currently requires the SGLang main branch. Switch to a stable SGLang release once Cosmos 3 support is included there.
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To serve the model on multiple GPUs:
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```bash
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sglang serve \
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--model-path nvidia/Cosmos3-Super \
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--num-gpus 4
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```
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