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{
"bomFormat": "CycloneDX",
"specVersion": "1.6",
"serialNumber": "urn:uuid:36ba7488-06f4-490d-9231-4fe7d5641554",
"version": 1,
"metadata": {
"timestamp": "2025-06-05T09:42:09.455907+00:00",
"component": {
"type": "machine-learning-model",
"bom-ref": "renderartist/simplevectorflux-e0c6eafc-2c9a-5ad1-8516-a7bf90b41353",
"name": "renderartist/simplevectorflux",
"externalReferences": [
{
"url": "https://huggingface.co/renderartist/simplevectorflux",
"type": "documentation"
}
],
"modelCard": {
"modelParameters": {
"task": "text-to-image"
},
"properties": [
{
"name": "library_name",
"value": "diffusers"
},
{
"name": "base_model",
"value": "black-forest-labs/FLUX.1-dev"
}
]
},
"authors": [
{
"name": "renderartist"
}
],
"licenses": [
{
"license": {
"name": "creativeml-openrail-m"
}
}
],
"description": "Simple Vector Flux was trained on a curated dataset of ~50 synthetic images in classic vector style, 17 epochs, 2 repeats, ~1700 steps.This is a work in progress and it can be a little temperamental, the captioning was done using Joy Caption Batch with the trigger "v3ct0r" and "vector" in the prefix of the captions.You have to work a little bit to get desired results and sometimes there is bleeding/blending of subjects but overall the style is present and the results can be really good. This LoRA takes a couple of tries adjusting your prompt and adding tokens to match the style.",
"tags": [
"diffusers",
"text-to-image",
"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:creativeml-openrail-m",
"region:us"
]
}
}
} |