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("huwhitememes/timwalz-lora")
prompt = "Tim Walz, black rimmed prescription glasses, ruffled business suite, loose tie, unbuttoned shirt, dirty clothes, down on his luck, sad, drunkard, wasted, sloppy drunk, neon street light, prostitutes in the background, city nightlife and crime scenery"
image = pipe(prompt).images[0]Timwalz Lora
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
Trigger words
You should use Tim Walz 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('huwhitememes/timwalz-lora', 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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Model tree for huwhitememes/timwalz-lora
Base model
black-forest-labs/FLUX.1-dev