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("jsapience/j-sapience-flux")
prompt = "jsapience"
image = pipe(prompt).images[0]j sapience flux
Model description
portrait model test
Trigger words
You should use jsapience to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-lora-fast-training.
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Base model
black-forest-labs/FLUX.1-dev