metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: >-
A black ford mustang parked in the parking lot, in the style of futurism
influence, uhd image, furaffinity, focus, street photography, thin steel
forms, 32k uhd --ar 2:3 --v 5
output:
url: images/qqq.png
- text: >-
Ferrari car f3 458 tt, in the style of liam wong, fujifilm x-t4, multiple
exposure, tsubasa nakai, uhd image, pinturicchio, crimson --ar 16:9 --v
5.2
output:
url: images/www.png
- text: Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k
output:
url: images/eee.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Car
license: creativeml-openrail-m
Car-Flux-Dev-LoRA
The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
Model description
prithivMLmods/Canopus-Car-Flux-Dev-LoRA
Image Processing Parameters
Parameter | Value | Parameter | Value |
---|---|---|---|
LR Scheduler | constant | Noise Offset | 0.03 |
Optimizer | AdamW8bit | Multires Noise Discount | 0.1 |
Network Dim | 64 | Multires Noise Iterations | 10 |
Network Alpha | 32 | Repeat & Steps | 22 & 1.5K+ |
Epoch | 15 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 40+ [ Hi-RES ]
& More ...............
Trigger prompts
A black ford mustang parked in the parking lot, in the style of futurism influence, uhd image, furaffinity, focus, street photography, thin steel forms, 32k uhd --ar 2:3 --v 5
Ferrari car f3 458 tt, in the style of liam wong, fujifilm x-t4, multiple exposure, tsubasa nakai, uhd image, pinturicchio, crimson --ar 16:9 --v 5.2
Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k
Parameter | Value |
---|---|
Prompt | Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k |
Sampler | euler |
Setting Up
import torch
from pipelines import DiffusionPipeline
base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Canopus-Car-Flux-Dev-LoRA"
trigger_word = "car" # Leave trigger_word blank if not used.
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Trigger words
You should use Car
to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.