metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
- Product-Ad
widget:
- text: >-
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.
output:
url: images/PA1.png
- text: >-
Product Ad, a blue and silver electric razor is soaring through the air.
The razor is positioned in the middle of a grassy field, with a backdrop
of a mountain range that is covered in snow. The sky is a deep blue,
dotted with white clouds, adding a pop of color to the scene. The blades
of the razor are splashing in the air, adding texture to the image.
output:
url: images/PA3.png
- text: >-
Product Ad,Vegan Snacks, in the style of an outdoors product hero shot in
motion, dynamic magazine ad image, photorealism, 4k Raw, --v6
output:
url: images/PA4.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Product Ad
license: creativeml-openrail-m
Flux-Product-Ad-Backdrop
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/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
Best Dimensions
- 768 x 1024 (Best)
- 1024 x 1024 (Default)
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/Flux-Product-Ad-Backdrop"
trigger_word = "Product Ad"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Trigger words
You should use Product Ad
to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.