diff-storyboard / examples /flux /model_inference /FLUX.1-dev-LoRA-Fusion.py
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import torch
from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig
pipe = FluxImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="flux1-dev.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/"),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
ModelConfig(model_id="DiffSynth-Studio/LoRAFusion-preview-FLUX.1-dev", origin_file_pattern="model.safetensors"),
],
)
pipe.enable_lora_magic()
pipe.load_lora(
pipe.dit,
ModelConfig(model_id="cancel13/cxsk", origin_file_pattern="30.safetensors"),
hotload=True,
)
pipe.load_lora(
pipe.dit,
ModelConfig(model_id="DiffSynth-Studio/ArtAug-lora-FLUX.1dev-v1", origin_file_pattern="merged_lora.safetensors"),
hotload=True,
)
image = pipe(prompt="a cat", seed=0)
image.save("image_fused.jpg")