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 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
Fix SGLang documentation links
Browse files
README.md
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- [PyTorch](https://github.com/nvidia/cosmos3)
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- [vLLM-Omni](https://github.com/vllm-project/vllm-omni)
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- [Hugging Face Diffusers](https://huggingface.co/docs/diffusers/en/index)
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- [SGLang](https://sgl-project
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**Supported Hardware Microarchitecture Compatibility:**
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### SGLang
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[SGLang Diffusion](https://
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```shell
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git clone --branch main https://github.com/sgl-project/sglang.git
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SGLang accepts Cosmos 3 request options including `max_sequence_length`, `flow_shift`, `extra_params.guardrails`, `extra_params.use_resolution_template`, and `extra_params.use_duration_template`. Video-to-video, video-with-sound, and action generation are not supported by SGLang yet.
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For complete serving instructions and request examples, see the [Cosmos3 SGLang cookbook](https://
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## Limitations
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## Inference
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**Acceleration Engine:** [PyTorch](https://pytorch.org/), [vLLM](https://github.com/vllm-project/vllm), [vLLM-Omni](https://github.com/vllm-project/vllm-omni), [Hugging Face Diffusers](https://github.com/huggingface/diffusers), [SGLang](https://sgl-project
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**Test Hardware:** GB200 and H100
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- [PyTorch](https://github.com/nvidia/cosmos3)
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- [vLLM-Omni](https://github.com/vllm-project/vllm-omni)
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- [Hugging Face Diffusers](https://huggingface.co/docs/diffusers/en/index)
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- [SGLang](https://github.com/sgl-project/sglang)
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**Supported Hardware Microarchitecture Compatibility:**
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### SGLang
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[SGLang Diffusion](https://docs.sglang.io/docs/sglang-diffusion/index) can serve `nvidia/Cosmos3-Nano` through OpenAI-compatible image and video generation endpoints. Install SGLang from the main branch with diffusion dependencies, then start a server:
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```shell
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git clone --branch main https://github.com/sgl-project/sglang.git
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SGLang accepts Cosmos 3 request options including `max_sequence_length`, `flow_shift`, `extra_params.guardrails`, `extra_params.use_resolution_template`, and `extra_params.use_duration_template`. Video-to-video, video-with-sound, and action generation are not supported by SGLang yet.
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For complete serving instructions and request examples, see the [Cosmos3 SGLang cookbook](https://docs.sglang.io/cookbook/diffusion/Cosmos/Cosmos3).
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## Limitations
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## Inference
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**Acceleration Engine:** [PyTorch](https://pytorch.org/), [vLLM](https://github.com/vllm-project/vllm), [vLLM-Omni](https://github.com/vllm-project/vllm-omni), [Hugging Face Diffusers](https://github.com/huggingface/diffusers), [SGLang](https://github.com/sgl-project/sglang), [SGLang Diffusion](https://docs.sglang.io/docs/sglang-diffusion/index)
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**Test Hardware:** GB200 and H100
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