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+ {
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+ "bomFormat": "CycloneDX",
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+ "specVersion": "1.6",
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+ "serialNumber": "urn:uuid:520aa74b-77fd-45ad-86f4-39110dbbcbda",
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+ "version": 1,
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+ "metadata": {
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+ "timestamp": "2025-06-05T09:36:18.912990+00:00",
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+ "component": {
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+ "type": "machine-learning-model",
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+ "bom-ref": "stabilityai/sd-turbo-ee31968f-8aa4-5c6d-827a-b66124849b83",
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+ "name": "stabilityai/sd-turbo",
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+ "externalReferences": [
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+ {
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+ "url": "https://huggingface.co/stabilityai/sd-turbo",
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+ "type": "documentation"
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+ }
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+ ],
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+ "modelCard": {
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+ "modelParameters": {
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+ "task": "text-to-image"
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+ },
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+ "properties": [
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+ {
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+ "name": "library_name",
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+ "value": "diffusers"
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+ }
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+ ]
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+ },
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+ "authors": [
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+ {
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+ "name": "stabilityai"
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+ }
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+ ],
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+ "description": "SD-Turbo is a distilled version of [Stable Diffusion 2.1](https://huggingface.co/stabilityai/stable-diffusion-2-1), trained for real-time synthesis.SD-Turbo is based on a novel training method called Adversarial Diffusion Distillation (ADD) (see the [technical report](https://stability.ai/research/adversarial-diffusion-distillation)), which allows sampling large-scale foundationalimage diffusion models in 1 to 4 steps at high image quality.This approach uses score distillation to leverage large-scale off-the-shelf image diffusion models as a teacher signal and combines this with anadversarial loss to ensure high image fidelity even in the low-step regime of one or two sampling steps.- **Developed by:** Stability AI- **Funded by:** Stability AI- **Model type:** Generative text-to-image model- **Finetuned from model:** [Stable Diffusion 2.1](https://huggingface.co/stabilityai/stable-diffusion-2-1)",
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+ "tags": [
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+ "diffusers",
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+ "safetensors",
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+ "text-to-image",
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+ "autotrain_compatible",
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+ "diffusers:StableDiffusionPipeline",
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+ "region:us"
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+ ]
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+ }
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+ }
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+ }