Flux LoRA Collections
Collection
Flux THE LoRA β’ 131 items β’ Updated β’ 33
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-Dev-Real-Anime-LoRA")
prompt = "A photo of an anime model wearing a trendy oversized sweater and denim shorts, sitting on a swing in a park with hands gripping the chains. The golden hour sunlight filters through the trees, creating a magical atmosphere. Fashion photography, high resolution, 35mm lens, f/2.8, natural lighting, global illumination. --ar 85:128 --v 6.0 --style raw."
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.
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-Dev-Real-Anime-LoRA"
trigger_word = "Real Anime" # Leave trigger_word blank if not used.
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
import gradio as gr
gr.load("prithivMLmods/Flux-Dev-Real-Anime-LoRA").launch()
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import gradio as gr
def image_generator(prompt):
pass
interface = gr.Interface(fn=image_generator, inputs="text", outputs="image")
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
app = gr.mount_gradio_app(app, interface, path="/")
/project-root/
β
βββ .gitattributes
βββ README.md
βββ app.py
βββ pythonproject.py
You should use Real Anime 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