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("fazemasta/birdcage")
prompt = "neon Maserati Birdcage driving at sunset"
image = pipe(prompt).images[0]Maserati Birdcage Flux LoRA
Trained on Weights.gg.
Used 15 pictures of the Maserati Birdcage 75th Concept.
Trigger words
You should use Birdcage to trigger the image generation.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('fazemasta/birdcage', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Base model
black-forest-labs/FLUX.1-dev