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README.md
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### Model Description
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black-forest-labs/FLUX.1-dev๋ฅผ ๊ธฐ๋ฐ์ผ๋ก Bingsu/clip-vit-large-patch14-ko๋ฅผ ์ ์ฉํ๊ณ , T5 Encoder์์ ํ๊ตญ์ด vocab ํ์ฅ์ ์ ์ฉํด์ fine-tuning(์ฝ๋ฉ ์ฟผํ ์ด์๋ก ์ธํด์, 1 X A100์ 2์๊ฐ ํ์ต) ์ ์ฉ
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### Model Description
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black-forest-labs/FLUX.1-dev๋ฅผ ๊ธฐ๋ฐ์ผ๋ก Bingsu/clip-vit-large-patch14-ko๋ฅผ ์ ์ฉํ๊ณ , T5 Encoder์์ ํ๊ตญ์ด vocab ํ์ฅ์ ์ ์ฉํด์ fine-tuning(์ฝ๋ฉ ์ฟผํ ์ด์๋ก ์ธํด์, 1 X A100์ 2์๊ฐ ํ์ต) ์ ์ฉ
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### example
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```
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import torch
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from diffusers import FluxPipeline
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pipe = FluxPipeline.from_pretrained("jaeyong2/FLUX.1-dev-ko", torch_dtype=torch.bfloat16)
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pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power
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prompt = "ํ๋ ์๋ฅผ ๋ฌ๋ฆฌ๋ ๊ณ ์์ด'"
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image = pipe(
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prompt,
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height=1024,
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width=1024,
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guidance_scale=3.5,
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num_inference_steps=50,
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max_sequence_length=512,
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generator=torch.Generator("cpu").manual_seed(0)
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).images[0]
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```
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