Instructions to use nvidia/difix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nvidia/difix 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/difix", 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
docs(support): add support routing
Browse files
README.md
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@@ -156,4 +156,16 @@ Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.
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| List types of specific high-risk AI systems, if any, in which the model can be integrated: | The model can be used to develop Autonomous Vehicles stacks that can be integrated inside vehicles. The Difix model should not be deployed in a vehicle. |
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| Describe the life critical impact (if present). | N/A - The model should not be deployed in a vehicle and will not perform life-critical tasks. |
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| Use Case Restrictions: | Your use of the model and code is governed by the NVIDIA License. Additional Information: LICENSE.md 路 stabilityai/sd-turbo at main |
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| Model and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to. |
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| List types of specific high-risk AI systems, if any, in which the model can be integrated: | The model can be used to develop Autonomous Vehicles stacks that can be integrated inside vehicles. The Difix model should not be deployed in a vehicle. |
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| Describe the life critical impact (if present). | N/A - The model should not be deployed in a vehicle and will not perform life-critical tasks. |
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| Use Case Restrictions: | Your use of the model and code is governed by the NVIDIA License. Additional Information: LICENSE.md 路 stabilityai/sd-turbo at main |
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| Model and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to. |
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## Support
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**DiFix is a previous-generation model:** please use [Fixer](https://github.com/nv-tlabs/Fixer) for active development and support.
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**Usage questions and discussion:** please post on the [NVIDIA Developer Forum (Omniverse / NuRec)](https://forums.developer.nvidia.com/c/omniverse/platform/nurec/752).
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**Code-level bugs, documentation issues, and feature requests:** file a [GitHub issue](https://github.com/nv-tlabs/Fixer/issues/new/choose) for Fixer using the appropriate template.
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**Security vulnerabilities:** use [NVIDIA's Vulnerability Disclosure Program](https://app.intigriti.com/programs/nvidia/nvidiavdp/detail). Do not file security issues publicly in this repository.
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*The Hugging Face Community tab for this model card will be disabled on 08/10/2026. Please use the channels above.*
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