FLUX.1-dev LoRAs
Collection
The prior-gen back-catalogue — FLUX.1-dev character & style LoRAs. • 55 items • Updated
How to use noema-art/maccinft 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("noema-art/maccinft")
prompt = "maccinft"
image = pipe(prompt).images[0]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("noema-art/maccinft")
prompt = "maccinft"
image = pipe(prompt).images[0]The maccinft LoRA model enables the generation of images in a unique custom style, characterized by vibrant colors and intricate detail. This model is ideal for artists and creators looking to infuse their work with a distinctive visual flair.
Trigger word: maccinft
.safetensors file from the Files tabComfyUI/models/loras/0.8-1.0maccinft in your promptimport torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
torch_dtype=torch.bfloat16
)
pipe.load_lora_weights("ms2stationthis/maccinft")
pipe.to("cuda")
image = pipe(
prompt="maccinft portrait, soft lighting, detailed",
guidance_scale=3.5-4.0,
num_inference_steps=20-30,
generator=torch.Generator("cuda").manual_seed(42)
).images[0]
image.save("output.png")
| Parameter | Value |
|---|---|
| LoRA Strength | 0.8-1.0 |
| Guidance Scale | 3.5-4.0 |
| Inference Steps | 20-30 |
| Resolution | 1024x1024 |
maccinft portrait, soft lighting, detailedmaccinft in a scenic environmentmaccinftTrained using StationThis — an AI creative platform powered by $MS2. Train your own LoRAs via @stationthisbot on Telegram.
Generated by StationThis Training Pipeline
Base model
black-forest-labs/FLUX.1-dev