| import torch |
| from diffsynth.pipelines.flux_image 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-Fill-dev", origin_file_pattern="flux1-fill-dev.safetensors"), |
| ModelConfig(model_id="black-forest-labs/FLUX.1-Fill-dev", origin_file_pattern="text_encoder/model.safetensors"), |
| ModelConfig(model_id="black-forest-labs/FLUX.1-Fill-dev", origin_file_pattern="text_encoder_2/*.safetensors"), |
| ModelConfig(model_id="black-forest-labs/FLUX.1-Fill-dev", origin_file_pattern="ae.safetensors"), |
| ], |
| ) |
| pipe.load_lora(pipe.dit, "models/train/FLUX.1-Fill-dev_lora/epoch-0.safetensors", alpha=1) |
|
|
| image = pipe( |
| prompt="a white paper cup", |
| flux_fill_image=Image.open("data/diffsynth_example_dataset/flux/FLUX.1-Fill-dev/cup.png").convert("RGB"), |
| flux_fill_mask=Image.open("data/diffsynth_example_dataset/flux/FLUX.1-Fill-dev/cup_mask.png").convert("L"), |
| height=1632, width=1232, |
| seed=0, embedded_guidance=30.0, num_inference_steps=50, |
| ) |
| image.save("image_FLUX.1-Fill-dev_lora.jpg") |
|
|
