Flux LoRA Collections
Collection
Flux THE LoRA • 131 items • Updated • 33
How to use prithivMLmods/Flux-Product-Ad-Backdrop with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("prithivMLmods/Flux-Product-Ad-Backdrop")
prompt = "Product Ad, Captured at eye-level, a close-up shot captures a pile of fried chicken wings in a white paper cup. The chicken wings are a vibrant brown color, adding a pop of color to the scene. The cup is placed on a light brown wooden table, creating a stark contrast with the vibrant blue sky in the background. To the right of the chicken wings, a slice of lemon, a red onion, and a red radish are placed on the table. The radish, and red onions are arranged in a circular pattern, adding depth to the composition. The backdrop is blurred, suggesting a fair day."
image = pipe(prompt).images[0]import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("prithivMLmods/Flux-Product-Ad-Backdrop")
prompt = "Product Ad, Captured at eye-level, a close-up shot captures a pile of fried chicken wings in a white paper cup. The chicken wings are a vibrant brown color, adding a pop of color to the scene. The cup is placed on a light brown wooden table, creating a stark contrast with the vibrant blue sky in the background. To the right of the chicken wings, a slice of lemon, a red onion, and a red radish are placed on the table. The radish, and red onions are arranged in a circular pattern, adding depth to the composition. The backdrop is blurred, suggesting a fair day."
image = pipe(prompt).images[0]


The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
prithivMLmods/Flux-Product-Ad-Backdrop
Image Processing Parameters
| Parameter | Value | Parameter | Value |
|---|---|---|---|
| LR Scheduler | constant | Noise Offset | 0.03 |
| Optimizer | AdamW | Multires Noise Discount | 0.1 |
| Network Dim | 64 | Multires Noise Iterations | 10 |
| Network Alpha | 32 | Repeat & Steps | 19 & 2970 |
| Epoch | 15 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 19
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/Flux-Product-Ad-Backdrop"
trigger_word = "Product Ad"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
You should use Product Ad to trigger the image generation.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Base model
black-forest-labs/FLUX.1-dev