metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: >-
Animeo, An animated animated image of a man with blonde hair and blue
eyes. He is wearing a purple hoodie with a hoodie underneath. His arms are
crossed over his chest and he is sitting on a black bench. Behind him is a
green wall and behind the wall are a row of skyscrapers. The sky is blue
with a few white clouds.
output:
url: images/A1.png
- text: >-
Animeo, An animated cartoon girl with long light blue hair, a pink tank
top, and black gloves. She is holding a red and white lollipop in her
right hand. The background is a dark blue.
output:
url: images/A3.png
- text: >-
Animeo, An animated image of an anime girl with long black hair and a bow
on her head. She is wearing a white dress with a blue belt around her
waist. The girls eyes are blue and she has a serious expression on her
face. The background is a vibrant blue with white letters that spell out
the word "RAIDEN".
output:
url: images/A4.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Animeo
license: apache-2.0
Model description
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 | 35 & 4700 |
Epoch | 22 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 50 [ 10@5 ] [ Hi -Res ]
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 = "strangerzonehf/Flux-Animeo-v1-LoRA"
trigger_word = "Animeo"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Trigger words
You should use Animeo
to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.