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---
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
<Gallery />
**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](/prithivMLmods/Canopus-Car-Flux-Dev-LoRA/tree/main) them in the Files & versions tab.
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