metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
- Yellow
- Lasers
- Flare
widget:
- text: >-
Yellow Lasers, Captured at eye-level on a low-angle perspective, a
night-time shot captures a glowing figure of a person running on a wet
concrete surface. The figure is adorned with a helmet, adorned with white
dots, and a long line of light trails behind it, adding a touch of
movement to the scene. The background is a deep black, creating a stark
contrast to the figure.
output:
url: images/YL1.png
- text: >-
Yellow Lasers, a black and white cat stands on its hind legs, facing the
left side of the frame. The cats back is facing the viewer, its front paws
are raised in the air, while its tail is stretched out in front of it. The
background is dark, creating a stark contrast to the cats body and the
lights in the background, adding a touch of color to the scene.
output:
url: images/YL2.png
- text: >-
Yellow Lasers, Captured from a low-angle perspective on a dark stage, a
white bicycle is positioned in the center of the frame. The bicycle is
adorned with two white lights, one on each side of its body and the other
on the back. The bike is positioned on two metal stands, creating a stark
contrast against the backdrop of the stage. Two men are standing on the
left side of the image, facing away from the camera on the right side.
They are dressed in dark clothing, with hats on their heads. A long black
cord is stretched across the stage, adding a touch of contrast to the
scene.
output:
url: images/YL3.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Yellow Lasers
license: creativeml-openrail-m
Yellow-Laser-Flux-LoRA
- Prompt
- Yellow Lasers, Captured at eye-level on a low-angle perspective, a night-time shot captures a glowing figure of a person running on a wet concrete surface. The figure is adorned with a helmet, adorned with white dots, and a long line of light trails behind it, adding a touch of movement to the scene. The background is a deep black, creating a stark contrast to the figure.
- Prompt
- Yellow Lasers, a black and white cat stands on its hind legs, facing the left side of the frame. The cats back is facing the viewer, its front paws are raised in the air, while its tail is stretched out in front of it. The background is dark, creating a stark contrast to the cats body and the lights in the background, adding a touch of color to the scene.
- Prompt
- Yellow Lasers, Captured from a low-angle perspective on a dark stage, a white bicycle is positioned in the center of the frame. The bicycle is adorned with two white lights, one on each side of its body and the other on the back. The bike is positioned on two metal stands, creating a stark contrast against the backdrop of the stage. Two men are standing on the left side of the image, facing away from the camera on the right side. They are dressed in dark clothing, with hats on their heads. A long black cord is stretched across the stage, adding a touch of contrast to the scene.
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/Yellow-Laser-Flux-LoRA
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 | 20 & 2000 |
| Epoch | 10 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 13
Best Dimensions
- 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/Yellow-Laser-Flux-LoRA"
trigger_word = "Yellow Lasers"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Trigger words
You should use Yellow Lasers to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.