{
    "bomFormat": "CycloneDX",
    "specVersion": "1.6",
    "serialNumber": "urn:uuid:d9fd9ecd-24d7-45fd-b99b-3387fdf9a4c8",
    "version": 1,
    "metadata": {
        "timestamp": "2025-07-10T08:48:58.434970+00:00",
        "component": {
            "type": "machine-learning-model",
            "bom-ref": "laion/CLIP-ViT-H-14-laion2B-s32B-b79K-1cc4816d-7985-5eff-adbc-1b0fca71fe35",
            "name": "laion/CLIP-ViT-H-14-laion2B-s32B-b79K",
            "externalReferences": [
                {
                    "url": "https://huggingface.co/laion/CLIP-ViT-H-14-laion2B-s32B-b79K",
                    "type": "documentation"
                }
            ],
            "modelCard": {
                "modelParameters": {
                    "task": "zero-shot-image-classification",
                    "architectureFamily": "clip",
                    "modelArchitecture": "CLIPModel"
                },
                "properties": [
                    {
                        "name": "library_name",
                        "value": "open_clip"
                    }
                ],
                "consideration": {
                    "useCases": "As per the original [OpenAI CLIP model card](https://github.com/openai/CLIP/blob/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1/model-card.md), this model is intended as a research output for research communities. We hope that this model will enable researchers to better understand and explore zero-shot, arbitrary image classification. We also hope it can be used for interdisciplinary studies of the potential impact of such model.The OpenAI CLIP paper includes a discussion of potential downstream impacts to provide an example for this sort of analysis. Additionally, the LAION-5B blog (https://laion.ai/blog/laion-5b/) and upcoming paper include additional discussion as it relates specifically to the training dataset."
                }
            },
            "authors": [
                {
                    "name": "laion"
                }
            ],
            "licenses": [
                {
                    "license": {
                        "id": "MIT",
                        "url": "https://spdx.org/licenses/MIT.html"
                    }
                }
            ],
            "description": "A CLIP ViT-H/14 model trained with the LAION-2B English subset of LAION-5B (https://laion.ai/blog/laion-5b/) using OpenCLIP (https://github.com/mlfoundations/open_clip).Model training done by Romain Beaumont on the [stability.ai](https://stability.ai/) cluster.",
            "tags": [
                "open_clip",
                "pytorch",
                "safetensors",
                "clip",
                "zero-shot-image-classification",
                "arxiv:1910.04867",
                "license:mit",
                "region:us"
            ]
        }
    }
}