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33 lines
1.5 KiB
Python
33 lines
1.5 KiB
Python
from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
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import torch
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vram_config = {
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"offload_dtype": "disk",
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"offload_device": "disk",
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"onload_dtype": torch.float8_e4m3fn,
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"onload_device": "cpu",
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"preparing_dtype": torch.float8_e4m3fn,
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"preparing_device": "cuda",
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"computation_dtype": torch.bfloat16,
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"computation_device": "cuda",
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}
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pipe = Flux2ImagePipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="black-forest-labs/FLUX.2-klein-9B", origin_file_pattern="text_encoder/*.safetensors", **vram_config),
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ModelConfig(model_id="black-forest-labs/FLUX.2-klein-9B", origin_file_pattern="transformer/*.safetensors", **vram_config),
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ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
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],
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tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
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vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
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)
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prompt = "Masterpiece, best quality. Anime-style portrait of a woman in a blue dress, underwater, surrounded by colorful bubbles."
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image = pipe(prompt, seed=0, rand_device="cuda", num_inference_steps=4)
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image.save("image_FLUX.2-klein-9B.jpg")
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prompt = "change the color of the clothes to red"
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image = pipe(prompt, edit_image=[image], seed=1, rand_device="cuda", num_inference_steps=4)
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image.save("image_edit_FLUX.2-klein-9B.jpg")
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