| import torch | |
| from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig | |
| from PIL import Image | |
| 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="InstantX/FLUX.1-dev-IP-Adapter", origin_file_pattern="ip-adapter.bin"), | |
| ModelConfig(model_id="google/siglip-so400m-patch14-384"), | |
| ], | |
| ) | |
| pipe.load_lora(pipe.dit, "models/train/FLUX.1-dev-IP-Adapter_lora/epoch-4.safetensors", alpha=1) | |
| image = pipe( | |
| prompt="dog,white and brown dog, sitting on wall, under pink flowers", | |
| ipadapter_images=Image.open("data/example_image_dataset/1.jpg"), | |
| height=768, width=768, | |
| seed=0 | |
| ) | |
| image.save("image_FLUX.1-dev-IP-Adapter_lora.jpg") | |