Flux LoRA Collections
Collection
Flux THE LoRA β’ 131 items β’ Updated β’ 33
How to use prithivMLmods/Flux-Toonic-2.5D-LoRA 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-Toonic-2.5D-LoRA")
prompt = "toonic 2.5D, Captured from a low-angle perspective on a vibrant yellow backdrop, a cartoon boy is depicted in a cartoon-like fashion. He is wearing a yellow shirt, blue pants, and white shoes. His arms are outstretched, and his mouth is slightly open, as if he is screaming. His eyes are squinted, and he has brown hair, and a black mustache. His hair is cut in a bob, adding a pop of color to the scene."
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-Toonic-2.5D-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 & 2900 |
| Epoch | 15 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 15
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-Toonic-2.5D-LoRA"
trigger_word = "toonic 2.5D"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
You should use toonic 2.5D 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