metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
- Red-Undersea
- Red-Theme
- Super-Red
widget:
- text: >-
Red Undersea, An eye-level perspective of a 3D image of a Burger. The
Burger is in the center of the image, with the Burger on the right side of
the frame and the Burger on the left side. There is a blue swirl in the
top left corner, and white swirls on the top right corner. There are red
swirls in the bottom left corner. The background is a deep blue, and there
are small white dots in the middle of the blue swirls. In the bottom right
corner, there is a black surface.
output:
url: images/RU1.png
- text: >-
Red Undersea, an illustration of a Tree in blue, in the style of glowing
neon, with fish fluid formation floating around, witchcore, dark cyan and
red, master of shadows, ethereal, ghostly figures
output:
url: images/RU5.png
- text: >-
Red Undersea, an illustration of a Candlelight in blue, in the style of
glowing neon, with fish fluid formation floating around, witchcore, dark
cyan and red, master of shadows, ethereal, ghostly figures
output:
url: images/RU6.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Red Undersea
license: creativeml-openrail-m
Red-Undersea-Flux-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/Red-Undersea-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 | 23 & 2600 |
Epoch | 12 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 13 [ Hi-RES ]
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/Red-Undersea-Flux-LoRA"
trigger_word = "Red Undersea"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Data source
- https://freeflo.ai/
Trigger words
You should use Red Undersea
to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.