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Airbrushed Shagin Wagon

73

Updated: May 16, 2025

vehicle

Download

1 variant available

SafeTensor

292.23 MB

Verified:

Type
LoRA
Stats

134

73

162

Reviews
Published

Dec 19, 2024

Base Model

Flux.1 D

Training
Steps: 2,430
Epochs: 15
Usage Tips
Clip Skip: 1
Strength: 1
Hash
AutoV2
72C7FCF4FC
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Followers - 4192

4.2K

Downloads - 70560

70.6K

Generations - 192307

192.3K

TheAlly's Granny Grippers!

The FLUX.1 [dev] Model is licensed by Black Forest Labs. Inc. under the FLUX.1 [dev] Non-Commercial License. Copyright Black Forest Labs. Inc.

IN NO EVENT SHALL BLACK FOREST LABS, INC. BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.

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Overview:
This model specializes in generating custom-painted retro vans featuring intricate airbrushed murals that seamlessly integrate with the vehicle's design and contours. The model captures the aesthetic of vintage 1970s and 1980s van art, providing customizable options for murals, color schemes, and van details, allowing for highly creative and detailed outputs.

Key Features:

  • Retro Van Shapes: Accurately reproduces classic van styles, including boxy designs, rounded edges, smooth side panels, and raised rooflines.

  • Custom Mural Integration: Generates highly detailed airbrushed murals that cover side panels, back doors, or wrap around the entire van. The murals blend naturally with the van's contours and surfaces.

  • Flexible Mural Styles: Offers versatility to create murals spanning various themes such as sci-fi, fantasy, nature, or abstract designs, with vibrant and cohesive color palettes.

  • Realistic Settings: Places vans in lifelike environments, including suburban driveways, car shows, grassy fields, and urban streets, with accurate lighting and reflections.

  • Customizable Details: Supports fine-tuning for color schemes, mural placement, and additional features like chrome accents, roof spoilers, and exhaust pipes.

Training Data:
The model was trained on a curated dataset of over 50 high-quality images of retro vans with diverse murals, focusing on realistic vehicle design, artistic mural integration, and environmental settings.