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Artiprocher
2025-11-19 20:22:21 +08:00
parent 6ad8d73717
commit eeb55a0ce6
88 changed files with 3113 additions and 78 deletions
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examples/flux/model_inference_low_vram/FLUX.1-dev-Controlnet-Upscaler.py Normal file
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import torch
from diffsynth.pipelines.flux_image import FluxImagePipeline, ModelConfig, ControlNetInput
vram_config = {
"onload_dtype": torch.float8_e4m3fn,
"onload_device": "cpu",
"onload_dtype": torch.float8_e4m3fn,
"onload_device": "cpu",
"preparing_dtype": torch.float8_e4m3fn,
"preparing_device": "cuda",
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
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", **vram_config),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors", **vram_config),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/*.safetensors", **vram_config),
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors", **vram_config),
ModelConfig(model_id="jasperai/Flux.1-dev-Controlnet-Upscaler", origin_file_pattern="diffusion_pytorch_model.safetensors", **vram_config),
],
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
)
image_1 = pipe(
prompt="a photo of a cat, highly detailed",
height=768, width=768,
seed=0, rand_device="cuda",
)
image_1.save("image_1.jpg")
image_1 = image_1.resize((2048, 2048))
image_2 = pipe(
prompt="a photo of a cat, highly detailed",
controlnet_inputs=[ControlNetInput(image=image_1, scale=0.7)],
input_image=image_1,
denoising_strength=0.99,
height=2048, width=2048, tiled=True,
seed=1, rand_device="cuda",
)
image_2.save("image_2.jpg")