{"id":212,"date":"2026-05-14T22:12:03","date_gmt":"2026-05-14T14:12:03","guid":{"rendered":"https:\/\/geocommunity.vip\/?p=212"},"modified":"2026-05-22T17:57:47","modified_gmt":"2026-05-22T09:57:47","slug":"f-polyimage%e4%ba%a7%e5%93%81%e8%b0%83%e7%94%a8%e4%ba%91gpu%e9%83%a8%e7%bd%b2%e7%9a%84%e8%a7%86%e8%a7%89%e6%a8%a1%e5%9e%8b%e5%8e%9f%e7%90%86","status":"publish","type":"post","link":"https:\/\/geocommunity.vip\/index.php\/2026\/05\/14\/f-polyimage%e4%ba%a7%e5%93%81%e8%b0%83%e7%94%a8%e4%ba%91gpu%e9%83%a8%e7%bd%b2%e7%9a%84%e8%a7%86%e8%a7%89%e6%a8%a1%e5%9e%8b%e5%8e%9f%e7%90%86\/","title":{"rendered":"F-PolyImage\u4ea7\u54c1\u4e91\u7aef\u89c6\u89c9\u6a21\u578b\u90e8\u7f72\u8c03\u7528\u3001Flux LoRA \u5fae\u8c03\u6700\u5feb\u4e0a\u624b\u6d41\u7a0b"},"content":{"rendered":"\n

\u672c\u6587\u4e2d\u51fa\u73b0\u7684 FPI \u7edf\u4e00\u6307\u4ee3 F-PolyImage \u4ea7\u54c1\uff08https:\/\/geocommunity.vip<\/a>\uff09<\/p>\n\n\n\n

\u9762\u5411\u8bfb\u8005\uff1a<\/strong>\u5982\u679c\u4f60\u6b63\u5728\u5c1d\u8bd5\u5feb\u901f\u90e8\u7f72\u89c6\u89c9\u5927\u6a21\u578b\uff0c\u5c06 AI \u56fe\u50cf\u751f\u6210\u80fd\u529b\u63a5\u5165\u81ea\u5df1\u7684\u4ea7\u54c1\uff0c\u6216\u8005\u5e0c\u671b\u540e\u7eed\u901a\u8fc7 LoRA \u5fae\u8c03\u8ba9\u6a21\u578b\u66f4\u8d34\u5408\u5177\u4f53\u4e1a\u52a1\u573a\u666f\uff0c\u90a3\u4e48\u8fd9\u7bc7\u6587\u7ae0\u4f1a\u6bd4\u8f83\u9002\u5408\u4f60\u3002\u672c\u6587\u4ee5 F-PolyImage \u4ea7\u54c1\u4e3a\u4f8b\uff0c\u8bb0\u5f55\u6211\u5982\u4f55\u5728\u4e91 GPU \u4e0a\u5b8c\u6210\u89c6\u89c9\u6a21\u578b\u7684\u90e8\u7f72\u4e0e\u5fae\u8c03\uff0c\u5e76\u501f\u52a9 ComfyUI \u5de5\u4f5c\u6d41\u548c API \u63a5\u53e3\uff0c\u8ba9\u524d\u7aef\u4ea7\u54c1\u80fd\u591f\u771f\u6b63\u8c03\u7528\u6a21\u578b\u751f\u6210\u56fe\u7247\u3002\u76f8\u6bd4\u5355\u7eaf\u4ecb\u7ecd\u67d0\u4e2a\u5de5\u5177\uff0c\u672c\u6587\u66f4\u5173\u6ce8\u4e00\u4e2a\u5b8c\u6574\u7684\u5de5\u7a0b\u5b9e\u8df5\u95ee\u9898\uff1a\u5982\u4f55\u628a\u4e00\u4e2a\u89c6\u89c9\u5927\u6a21\u578b\u4ece\u201c\u80fd\u8dd1\u8d77\u6765\u201d\uff0c\u8fdb\u4e00\u6b65\u63a8\u8fdb\u5230\u201c\u80fd\u88ab\u4ea7\u54c1\u7a33\u5b9a\u8c03\u7528\u201d\u3002<\/p>\n\n\n\n

\u4e00\u3001\u4e3a\u4ec0\u4e48\u73b0\u9636\u6bb5FPI\u9009\u62e9\u79df\u7528\u670d\u52a1\u5668\u6765\u505a\u6a21\u578b\u5fae\u8c03\uff0c\u800c\u4e0d\u76f4\u63a5\u81ea\u5efa\u7b97\u529b\u6216\u53ea\u7528\u7b2c\u4e09\u65b9 API\uff1f<\/h3>\n\n\n\n

\u76ee\u524d\u4ea7\u54c1\u4e0a\u7ebf\u65f6\u95f4\u8f83\u77ed\uff0c\u7528\u6237\u4f53\u91cf\u5c1a\u5c0f\uff0c\u540c\u65f6\u6211\u4eec\u5b58\u5728\u81ea\u7814\u90e8\u7f72\u6a21\u578b\u7684\u4e1a\u52a1\u9700\u6c42\u3002\u901a\u8fc7\u81ea\u4e3b\u5b8c\u6210\u6a21\u578b\u5fae\u8c03\u4e0e\u53c2\u6570\u5b9a\u5236\uff0c\u80fd\u591f\u6253\u9020\u4ea7\u54c1\u5dee\u5f02\u5316\u7ade\u4e89\u529b\uff0c\u6446\u8131\u5355\u7eaf\u4f9d\u8d56\u7b2c\u4e09\u65b9\u5927\u6a21\u578b API \u8c03\u7528\u7684\u88ab\u52a8\u5c40\u9762\u3002\u57fa\u4e8e\u73b0\u9636\u6bb5\u5b9e\u9645\u60c5\u51b5\uff0c\u6211\u4eec\u9009\u62e9\u4ee5\u670d\u52a1\u5668\u79df\u8d41\u65b9\u5f0f\u5f00\u5c55\u6a21\u578b\u5fae\u8c03\u53ca\u53c2\u6570\u4f18\u5316\u5de5\u4f5c\u3002<\/p>\n\n\n\n

\u4e8c\u3001\u6211\u4eec\u7684\u670d\u52a1\u5668\u662f\u5728\u54ea\u91cc\u79df\u7528\u7684\uff1f\u5e76\u7b80\u5355\u4ecb\u7ecdGPU\u3001CPU\u3001ComfyUI\u3002<\/h3>\n\n\n\n

\u6211\u4eec\u7684\u670d\u52a1\u5668\u79df\u7528\u81ea Onething AI\uff0c\u7ba1\u7406\u540e\u53f0\u5730\u5740\uff1ahttps:\/\/console.onethingai.com<\/a>\u3002\u521b\u5efa\u5b9e\u4f8b\uff0c\u9009\u62e9\u5408\u9002\u4e8e\u9700\u6c42\u7684\u955c\u50cf\u548c\u663e\u5361\u89c4\u683c\u5373\u53ef\u3002\u6211\u4eec\u7684\u5982\u4e0b\uff1a<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

ComfyUI<\/strong> \u662f\u4e00\u4e2a\u7528\u6765\u8fd0\u884c AI \u7ed8\u56fe\/\u56fe\u50cf\u751f\u6210\u5de5\u4f5c\u6d41\u7684\u53ef\u89c6\u5316\u5de5\u5177\u3002<\/p>\n\n\n\n

GPU<\/strong> \u7684\u5168\u79f0\u662f Graphics Processing Unit\uff0c\u4e2d\u6587\u5e38\u53eb \u56fe\u5f62\u5904\u7406\u5668 \/ \u663e\u5361\u3002\u4e3b\u653b\uff1a\u56fe\u50cf\u6e32\u67d3\u3001AI \u8ba1\u7b97\u3001\u5927\u91cf\u5e76\u884c\u8fd0\u7b97<\/p>\n\n\n\n

CPU<\/strong> \u7684\u5168\u79f0\u662f Central Processing Unit\uff0c\u4e2d\u6587\u53eb \u4e2d\u592e\u5904\u7406\u5668\u3002\u8d1f\u8d23\u8fd0\u884c\u7cfb\u7edf\u3001\u8c03\u5ea6\u7a0b\u5e8f\u3001\u5904\u7406\u901a\u7528\u8ba1\u7b97\u4efb\u52a1\u3002<\/p>\n\n\n\n

\u5176\u5b9e\u6211\u4eec\u5728 OneThing AI \u79df\u7528\u7684\u662f\u4e00\u4e2a\u5b8c\u6574\u7684\u4e91\u670d\u52a1\u5668\u5b9e\u4f8b\uff0c\u53ea\u4e0d\u8fc7\u5b83\u548c\u4e4b\u524d\u7528\u6765\u90e8\u7f72\u7f51\u7ad9\u7684\u817e\u8baf\u4e91\u670d\u52a1\u5668\u4e0d\u592a\u4e00\u6837\uff1a\u5b83\u914d\u5907\u4e86\u9ad8\u6027\u80fd GPU\uff0c\u56e0\u6b64\u66f4\u9002\u5408\u89c6\u89c9\u6a21\u578b\u3001AI \u7ed8\u56fe\u3001\u6a21\u578b\u63a8\u7406\u3001\u90e8\u7f72\u548c\u8c03\u53c2\u7b49\u4efb\u52a1\u3002<\/p>\n\n\n\n

\u4e09\u3001\u4e91\u670d\u52a1\u5668\u5728\u6a21\u578b\u90e8\u7f72\u65b9\u9762\u6709\u54ea\u4e9b\u64cd\u4f5c\u4e0a\u7684\u4f18\u52bf\uff1f\u6a21\u578b\u90e8\u7f72\u5230\u5e95\u90e8\u7f72\u7684\u662f\u4ec0\u4e48\uff1f<\/h3>\n\n\n\n

OneThing AI \u63d0\u4f9b\u7684\u662f\u4e00\u4e2a\u5df2\u7ecf\u90e8\u7f72\u597d\u7684 GPU + ComfyUI \u73af\u5883\uff0c\u6a21\u578b\u5982\u679c\u5df2\u5185\u7f6e\u5c31\u53ef\u4ee5\u76f4\u63a5\u9009\u7528\uff1b\u5982\u679c\u6ca1\u6709\u5185\u7f6e\uff0c\u5219\u9700\u8981\u5148\u4e0a\u4f20\u6216\u4e0b\u8f7d\u6a21\u578b\uff0c\u518d\u5728\u5bf9\u5e94\u5de5\u4f5c\u6d41\u4e2d\u8c03\u7528\u3002\u6a21\u578b\u90e8\u7f72\u4e0d\u662f\u4ece\u96f6\u5b89\u88c5\u670d\u52a1\u5668\u73af\u5883\u90a3\u4e00\u6b65\uff0c\u800c\u662f\u628a\u6a21\u578b\u6587\u4ef6\u51c6\u5907\u597d\uff0c\u5e76\u8ba9 ComfyUI \u80fd\u591f\u8c03\u7528\u5b83\u7684\u8fc7\u7a0b\u3002\u5982\u679c\u81ea\u5df1\u90e8\u7f72\uff1a\u51c6\u5907\u786c\u4ef6 \u2192 \u5b89\u88c5\u7cfb\u7edf \u2192 \u5b89\u88c5 GPU \u9a71\u52a8 \u2192 \u5b89\u88c5 CUDA \/ PyTorch \u73af\u5883 \u2192 \u5b89\u88c5 ComfyUI \u2192 \u4e0b\u8f7d\u6a21\u578b \u2192 \u653e\u5230\u6b63\u786e\u76ee\u5f55 \u2192 \u5b89\u88c5\u81ea\u5b9a\u4e49\u8282\u70b9 \u2192 \u542f\u52a8\u670d\u52a1 \u2192 \u6d4b\u8bd5\u5de5\u4f5c\u6d41 \u2192 \u5bf9\u5916\u8bbf\u95ee\u6216\u63a5\u5165\u4e1a\u52a1\u7cfb\u7edf\u3002\u53ef\u4ee5\u770b\u5230\u5f88\u590d\u6742\uff0c\u4f46\u662f\u90e8\u7f72\u539f\u7406\u90fd\u4e00\u6837\u3002<\/p>\n\n\n\n

\u56db\u3001FLUX.2 klein 4B + ComfyUI \u90e8\u7f72\u547d\u4ee4\u6559\u7a0b<\/h3>\n\n\n\n

\u6211\u4eec\u79df\u7528\u7684\u670d\u52a1\u5668\u652f\u6301 FLUX2 \u6a21\u578b\u7684\u5feb\u901f\u90e8\u7f72\uff0c\u56e0\u6b64\u5f53\u524d\u76ee\u6807\u662f\u5b8c\u6210\u5b98\u65b9\u5de5\u4f5c\u6d41\u7684\u914d\u7f6e\u4e0e\u5bfc\u5165\uff0c\u5177\u4f53\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n\n\n\n

    \n
  • \u4e0b\u8f7d\u5b98\u65b9\u5de5\u4f5c\u6d41 JSON<\/li>\n\n\n\n
  • \u590d\u5236\u5230 ComfyUI\/output<\/li>\n\n\n\n
  • \u4ece OneThingAI \u7684\u300c\u8f93\u51fa\u76ee\u5f55\u300d\u4e0b\u8f7d\u5230\u672c\u5730<\/li>\n\n\n\n
  • \u518d\u628a\u8fd9\u4e2a JSON \u62d6\u8fdb ComfyUI \u753b\u5e03<\/li>\n<\/ul>\n\n\n\n

    \u8be6\u7ec6\u90e8\u7f72\u8fc7\u7a0b\uff1a<\/p>\n\n\n\n

    \u9996\u5148\u8fdb\u5165\u547d\u4ee4\u884c\u754c\u9762\u3002<\/p>\n\n\n

    \n
    \"\"<\/figure>\n<\/div>\n\n\n

    \uff08\u70b9\u51fb”\u65e5\u5fd7\/\u7ec8\u7aef”\uff09<\/p>\n\n\n

    \n
    \"\"<\/figure>\n<\/div>\n\n\n

    1\u3001\u786e\u8ba4\u73af\u5883<\/h4>\n\n\n\n
    nvidia-smi<\/code><\/pre>\n\n\n\n
    \u786e\u8ba4\u80fd\u770b\u5230\uff1a<\/p>\n\n\n\n
    NVIDIA GeForce RTX 4090<\/code><\/pre>\n\n\n\n
    \u627e\u5230 ComfyUI \u76ee\u5f55\uff1a<\/p>\n\n\n\n
    find \/ -maxdepth 3 -type d -name \"ComfyUI\" 2>\/dev\/null<\/code><\/pre>\n\n\n\n
    \u4f60\u5f53\u65f6\u5f97\u5230\u7684\u662f\uff1a<\/p>\n\n\n\n
    \/root\/ComfyUI<\/code><\/pre>\n\n\n\n
    \u786e\u8ba4\u4e91\u5b58\u50a8\uff1a<\/p>\n\n\n\n
    ls \/root\/onethingai-fs\ndf -h | grep onethingai<\/code><\/pre>\n\n\n\n
    2\u3001\u521b\u5efa\u6a21\u578b\u76ee\u5f55\u5e76\u8f6f\u94fe\u63a5\u5230 ComfyUI<\/h4>\n\n\n\n
    mkdir -p \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models
    mkdir -p \/root\/onethingai-fs\/mymodels\/flux2\/text_encoders
    mkdir -p \/root\/onethingai-fs\/mymodels\/flux2\/vae<\/code><\/pre>\n\n\n\n
    \u628a ComfyUI \u7684\u6a21\u578b\u76ee\u5f55\u94fe\u63a5\u5230\u4e91\u5b58\u50a8\uff1a<\/p>\n\n\n\n
    cd \/root\/ComfyUI

    rm -rf \/root\/ComfyUI\/models\/diffusion_models
    ln -s \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models \/root\/ComfyUI\/models\/diffusion_models

    rm -rf \/root\/ComfyUI\/models\/text_encoders
    ln -s \/root\/onethingai-fs\/mymodels\/flux2\/text_encoders \/root\/ComfyUI\/models\/text_encoders

    rm -rf \/root\/ComfyUI\/models\/vae
    ln -s \/root\/onethingai-fs\/mymodels\/flux2\/vae \/root\/ComfyUI\/models\/vae<\/code><\/pre>\n\n\n\n
    \u68c0\u67e5\uff1a<\/p>\n\n\n\n
    ls -l \/root\/ComfyUI\/models | grep -E \"diffusion_models|text_encoders|vae\"<\/code><\/pre>\n\n\n\n
    3\u3001\u5b89\u88c5\u4e0b\u8f7d\u5de5\u5177<\/h4>\n\n\n\n
    python -m pip install -U modelscope
    python -m pip install -U \"huggingface_hub>=0.34.0,<1.0\"<\/code><\/pre>\n\n\n\n
    \u5982\u679c\u6ca1\u6709 aria2c<\/code>\uff0c\u5b89\u88c5\uff1a<\/p>\n\n\n\n
    apt update && apt install -y aria2<\/code><\/pre>\n\n\n\n
    4\u3001\u514b\u9686 FLUX.2 klein \u5de5\u4f5c\u6d41\u5305<\/h4>\n\n\n\n
    \u4f60\u5f53\u65f6\u4e0b\u8f7d\u7684\u662f\u8fd9\u4e2a\u5305\uff0c\u91cc\u9762\u6709\u5b98\u65b9\u5de5\u4f5c\u6d41\u548c\u4e0b\u8f7d\u94fe\u63a5\uff1a\n\ncd \/root\/onethingai-fs\/mymodels\n\ngit clone https:\/\/cnb.cool\/fuyaotingyu\/ComfyUI\/ComfyUI-FLUX.2-klein.git flux2_klein_pack\n\n\u8fdb\u5165\u76ee\u5f55\uff1a\n\ncd \/root\/onethingai-fs\/mymodels\/flux2_klein_pack\n\n\u67e5\u770b\u91cc\u9762\u7684\u6587\u4ef6\uff1a\n\nfind \/root\/onethingai-fs\/mymodels\/flux2_klein_pack -maxdepth 3 -type f | sort\n\n\u5f53\u65f6\u91cc\u9762\u6709\u8fd9\u4e2a\u5de5\u4f5c\u6d41\uff1a\n\nworkflows\/FLUX.2 klein \u84b8\u998f\u7248\u6587\u751f\u56fe.json<\/code><\/pre>\n\n\n\n
    5\u3001\u4e0b\u8f7d qwen_3_4b.safetensors<\/h4>\n\n\n\n
    \u8fd9\u662f\u6587\u672c\u7f16\u7801\u5668\uff0c\u5fc5\u987b\u662f\u5355\u6587\u4ef6\u7248\uff0c\u4e0d\u80fd\u7528 model-00001-of-00002.safetensors<\/code> \u90a3\u79cd\u5206\u7247\u6587\u4ef6\u3002<\/p>\n\n\n\n
    aria2c \\
      -x 16 \\
      -s 16 \\
      --continue=true \\
      --file-allocation=none \\
      -d \/root\/ComfyUI\/models\/text_encoders \\
      -o qwen_3_4b.safetensors \\
      \"https:\/\/cnb.cool\/ai-models\/Comfy-Org\/flux2-klein-4B\/-\/lfs\/6c671498573ac2f7a5501502ccce8d2b08ea6ca2f661c458e708f36b36edfc5a?name=qwen_3_4b.safetensors\"<\/code><\/pre>\n\n\n\n
    \u68c0\u67e5\uff1a<\/p>\n\n\n\n
    ls -lh \/root\/ComfyUI\/models\/text_encoders\/qwen_3_4b.safetensors<\/code><\/pre>\n\n\n\n
    6\u3001\u4e0b\u8f7d FLUX.2 klein 4B FP8 \u4e3b\u6a21\u578b<\/h4>\n\n\n\n
    \u8fd9\u662f\u540e\u6765\u89e3\u51b3\u663e\u5b58\u95ee\u9898\u7684\u5173\u952e\u6587\u4ef6\uff1a<\/p>\n\n\n\n
    cd \/root\/ComfyUI\/models\/diffusion_models

    aria2c -x 16 -s 16 -c \\
    -o flux-2-klein-4b-fp8.safetensors \\
    \"https:\/\/cnb.cool\/ai-models\/black-forest-labs\/FLUX.2-klein-4b-fp8\/-\/lfs\/97ed34fe0567e436200f2faee3939b88f2b5d99f8af2a4dc16532c4245c0ccb6?name=flux-2-klein-4b-fp8.safetensors\"<\/code><\/pre>\n\n\n\n
    \u68c0\u67e5\uff1a<\/p>\n\n\n\n
    ls -lh \/root\/ComfyUI\/models\/diffusion_models\/flux-2-klein-4b-fp8.safetensors<\/code><\/pre>\n\n\n\n
    \u4f60\u5f53\u65f6\u68c0\u67e5\u5230\uff1a<\/p>\n\n\n\n
    3.8G  flux-2-klein-4b-fp8.safetensors<\/code><\/pre>\n\n\n\n
    7\u3001\u4e0b\u8f7d\u6216\u51c6\u5907 VAE<\/h4>\n\n\n\n
    \u4f60\u5f53\u65f6\u5df2\u7ecf\u6709\u4e86\uff1a<\/p>\n\n\n\n
    flux2-vae.safetensors<\/code><\/pre>\n\n\n\n
    \u5982\u679c\u662f\u4ece ModelScope \u4e0b\u8f7d\uff0c\u53ef\u4ee5\u8fd9\u6837\uff1a<\/p>\n\n\n\n
    modelscope download --model black-forest-labs\/FLUX.2-klein-4B --include \"*.safetensors\" --local_dir \/root\/onethingai-fs\/mymodels\/flux2_test<\/code><\/pre>\n\n\n\n
    \u7136\u540e\u590d\u5236 VAE\uff1a<\/p>\n\n\n\n
    cp \/root\/onethingai-fs\/mymodels\/flux2_test\/vae\/diffusion_pytorch_model.safetensors \/root\/ComfyUI\/models\/vae\/flux2-vae.safetensors<\/code><\/pre>\n\n\n\n
    \u68c0\u67e5\uff1a<\/p>\n\n\n\n
    ls -lh \/root\/ComfyUI\/models\/vae\/flux2-vae.safetensors<\/code><\/pre>\n\n\n\n
    8\u3001\u628a\u5b98\u65b9\u5de5\u4f5c\u6d41\u590d\u5236\u5230 ComfyUI \u8f93\u51fa\u76ee\u5f55<\/h4>\n\n\n\n
    cp \"\/root\/onethingai-fs\/mymodels\/flux2_klein_pack\/workflows\/FLUX.2 klein \u84b8\u998f\u7248\u6587\u751f\u56fe.json\" \/root\/ComfyUI\/output\/flux2_official_t2i.json<\/code><\/pre>\n\n\n\n
    \u68c0\u67e5\uff1a<\/p>\n\n\n\n
    ls -lh \/root\/ComfyUI\/output\/flux2_official_t2i.json<\/code><\/pre>\n\n\n\n
    \u4f60\u5f53\u65f6\u5f97\u5230\uff1a<\/p>\n\n\n\n
    -rw-r--r-- 1 root root 18K ... \/root\/ComfyUI\/output\/flux2_official_t2i.json<\/code><\/pre>\n\n\n\n
    \u7136\u540e\u53bb OneThingAI \u9875\u9762\uff1a<\/p>\n\n\n\n
    \u8f93\u51fa\u76ee\u5f55 -> \u4e0b\u8f7d flux2_official_t2i.json \u5230\u672c\u5730<\/code><\/pre>\n\n\n\n
    \u518d\u628a\u8fd9\u4e2a\u6587\u4ef6\uff1a<\/p>\n\n\n\n
    flux2_official_t2i.json<\/code><\/pre>\n\n\n\n
    \u62d6\u8fdb ComfyUI \u753b\u5e03\uff0c\u5c31\u4f1a\u81ea\u52a8\u751f\u6210\u5982\u4e0b\u622a\u56fe\u7684\u8282\u70b9\u3002<\/p>\n\n\n\n
    \"\"<\/figure>\n\n\n\n
    9\u3001\u542f\u52a8\u6216\u91cd\u542f ComfyUI<\/h4>\n\n\n\n
    cd \/root\/ComfyUI\n\npkill -f \"python.*main.py\" || true\n\nsleep 2\n\nnohup python main.py --listen 0.0.0.0 --port 8188 > \/root\/comfyui.log 2>&1 &\n\nsleep 5\n\nss -lntp | grep 8188<\/code><\/pre>\n\n\n\n
    \u5f53\u7136\uff0c\u4e5f\u53ef\u4ee5\u5feb\u6377\u91cd\u542f\uff1a<\/p>\n\n\n
    \n
    \"\"<\/figure>\n<\/div>\n\n\n
    \u7136\u540e\u6839\u636e\u81ea\u8eab\u9700\u6c42\u8fdb\u884c\u8c03\u53c2\u5373\u53ef\u3002\u6240\u6709\u5de5\u4f5c\u5b8c\u6210\u4e4b\u540e\uff0c\u70b9\u51fb\u542f\u52a8\u6309\u94ae\uff0c\u6d4b\u8bd5\u56fe\u7247\u751f\u6210\u3002<\/p>\n\n\n\n
    \u4e94\u3001\u5de5\u4f5c\u6d41\u4ecb\u7ecd<\/h3>\n\n\n
    \n
    \"\"<\/figure>\n<\/div>\n\n\n
    1\u3001\u7b80\u5355\u4ecb\u7ecd<\/h4>\n\n\n\n
    \u4e00\u5957 FLUX.2 klein \u84b8\u998f\u7248\u6587\u751f\u56fe\u5de5\u4f5c\u6d41\u3002<\/p>\n\n\n\n
    \u5b83\u7684\u4f5c\u7528\u5f88\u7b80\u5355\uff1a\u8f93\u5165\u4e00\u6bb5\u6587\u5b57\u63d0\u793a\u8bcd\uff0c\u8ba9\u6a21\u578b\u6839\u636e\u63d0\u793a\u8bcd\u751f\u6210\u4e00\u5f20\u56fe\u7247\u3002<\/p>\n\n\n\n
    \u6bd4\u5982\u8fd9\u91cc\u7684\u63d0\u793a\u8bcd\u662f\uff1a\u4e00\u8f86\u8d85\u7ea7\u8dd1\u8f66\u3002<\/p>\n\n\n\n
    \u6574\u4e2a\u6d41\u7a0b\u53ef\u4ee5\u7406\u89e3\u4e3a\uff1a\u6587\u5b57\u63d0\u793a\u8bcd \u2192 \u6a21\u578b\u7406\u89e3\u6587\u5b57 \u2192 \u5728\u6f5c\u7a7a\u95f4\uff08Latent\uff09\u751f\u6210\u56fe\u50cf \u2192 \u89e3\u7801\u6210\u771f\u5b9e\u56fe\u7247 \u2192 \u4fdd\u5b58\u8f93\u51fa<\/p>\n\n\n\n
    2\u3001\u8be6\u53c2\u4ecb\u7ecd<\/h4>\n\n\n\n
    \u6a21\u5757<\/th>\u5f53\u524d\u914d\u7f6e(\u6839\u636e\u9700\u6c42\u8bbe\u7f6e)<\/th>\u6559\u5b66\u89e3\u91ca<\/th><\/tr><\/thead>
    \u5de5\u4f5c\u6d41\u7c7b\u578b<\/td>FLUX.2 klein \u6587\u751f\u56fe<\/td>\u6839\u636e\u6587\u5b57\u751f\u6210\u56fe\u7247<\/td><\/tr>
    \u63d0\u793a\u8bcd<\/td>\u4e00\u8f86\u8d85\u7ea7\u8dd1\u8f66<\/td>\u751f\u6210\u5185\u5bb9<\/td><\/tr>
    \u56fe\u7247\u5c3a\u5bf8<\/td>512\u00d7512<\/td>\u751f\u6210\u6b63\u65b9\u5f62\u56fe\u7247<\/td><\/tr>
    \u4e3b\u6a21\u578b<\/td>flux-2-klein-4b-fp8<\/td>\u8d1f\u8d23\u56fe\u50cf\u751f\u6210<\/td><\/tr>
    \u6587\u672c\u7f16\u7801\u5668<\/td>qwen_3_4b.safetensors<\/td>\u8d1f\u8d23\u7406\u89e3\u63d0\u793a\u8bcd<\/td><\/tr>
    VAE<\/td>flux2-vae.safetensors<\/td>\u8d1f\u8d23\u89e3\u7801\u56fe\u50cf<\/td><\/tr>
    Seed<\/td>randomize<\/td>\u6bcf\u6b21\u751f\u6210\u4e0d\u540c\u7ed3\u679c<\/td><\/tr>
    \u91c7\u6837\u5668<\/td>euler<\/td>\u5feb\u901f\u7a33\u5b9a\u7684\u91c7\u6837\u7b97\u6cd5<\/td><\/tr>
    \u6b65\u6570<\/td>4<\/td>\u84b8\u998f\u6a21\u578b\u5feb\u901f\u51fa\u56fe<\/td><\/tr>
    CFG<\/td>1.0<\/td>\u63d0\u793a\u8bcd\u5f15\u5bfc\u8f83\u81ea\u7136<\/td><\/tr>
    batch size<\/td>1<\/td>\u4e00\u6b21\u751f\u6210\u4e00\u5f20<\/td><\/tr>
    \u8f93\u51fa\u524d\u7f00<\/td>F-PolyImage<\/td>\u4fdd\u5b58\u56fe\u7247\u540d\u79f0\u524d\u7f00<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
    \u5982\u679c\u60f3\u6362\u66f4\u5f3a\u7684\u6a21\u578b\uff0c\u6bd4\u5982\u66f4\u5927\u53c2\u6570\u3001\u66f4\u9ad8\u7cbe\u5ea6\u3001\u753b\u8d28\u66f4\u597d\u7684 FLUX \u6a21\u578b\uff0c\u672c\u8d28\u4e0a\u5c31\u662f\uff1a\u628a UNet \u52a0\u8f7d\u5668\u91cc\u7684\u6a21\u578b\u6587\u4ef6\u6362\u6210\u53e6\u4e00\u4e2a\u6a21\u578b\u6587\u4ef6\u3002\u4f46\u524d\u63d0\u662f\uff1a\u8fd9\u4e2a\u6a21\u578b\u6587\u4ef6\u5fc5\u987b\u5df2\u7ecf\u5728\u670d\u52a1\u5668\u7684\u5bf9\u5e94\u6a21\u578b\u76ee\u5f55\u91cc\u3002<\/p>\n\n\n\n
    \u5982\u679c\u9700\u6c42\u662f\u56fe\u751f\u56fe\u6216\u8005\u5c40\u90e8\u91cd\u7ed8\uff0c\u90a3\u4e48\u5c31\u4e0d\u80fd\u53ea\u4f7f\u7528\u5f53\u524d\u8fd9\u5957\u6587\u751f\u56fe\u5de5\u4f5c\u6d41\uff0c\u800c\u5e94\u8be5\u5207\u6362\u5230\u5bf9\u5e94\u7684 Img2Img \u56fe\u751f\u56fe\u5de5\u4f5c\u6d41 \u6216 Inpainting \u5c40\u90e8\u91cd\u7ed8\u5de5\u4f5c\u6d41\u3002\uff08\u8be6\u60c5\u95eeGPT\uff0c\u8fd9\u91cc\u4e3b\u8981\u662f\u60f3\u544a\u8bc9\u5927\u5bb6\uff1a\u4e0d\u540c\u7684\u751f\u6210\u9700\u6c42\uff0c\u5bf9\u5e94\u7684\u662f\u4e0d\u540c\u7c7b\u578b\u7684\u5de5\u4f5c\u6d41\u3002\u6bd4\u5982\u6587\u751f\u56fe\u7528 Text-to-Image \u5de5\u4f5c\u6d41\uff0c\u56fe\u751f\u56fe\u7528 Img2Img \u5de5\u4f5c\u6d41\uff0c\u5c40\u90e8\u91cd\u7ed8\u7528 Inpainting \u5de5\u4f5c\u6d41\u3002\u5728\u5b9e\u9645\u4f7f\u7528\u4e2d\uff0c\u6548\u7387\u6700\u9ad8\u7684\u65b9\u5f0f\u901a\u5e38\u4e0d\u662f\u4ece\u96f6\u5f00\u59cb\u642d\u5efa\u8282\u70b9\uff0c\u800c\u662f\u4f18\u5148\u9009\u62e9\u5b98\u65b9\u5df2\u7ecf\u63d0\u4f9b\u597d\u7684\u5de5\u4f5c\u6d41\u6a21\u677f\uff0c\u7136\u540e\u5728\u8fd9\u4e2a\u57fa\u7840\u4e0a\u8c03\u6574\u63d0\u793a\u8bcd\u3001\u6a21\u578b\u3001\u5c3a\u5bf8\u3001\u6b65\u6570\u3001CFG\u3001\u53bb\u566a\u5f3a\u5ea6\u7b49\u5173\u952e\u53c2\u6570\u3002\u8fd9\u6837\u65e2\u80fd\u51cf\u5c11\u642d\u5efa\u8282\u70b9\u65f6\u51fa\u9519\u7684\u6982\u7387\uff0c\u4e5f\u80fd\u5e2e\u52a9\u6211\u4eec\u66f4\u5feb\u5730\u8dd1\u901a\u6d41\u7a0b\u3001\u9a8c\u8bc1\u6548\u679c\uff0c\u5e76\u628a\u4e3b\u8981\u7cbe\u529b\u653e\u5728\u6a21\u578b\u6548\u679c\u548c\u53c2\u6570\u8c03\u4f18\u4e0a\u3002\uff09<\/p>\n\n\n\n
    \u516d\u3001\u672c\u5730\u8dd1\u901a\u6587\u751f\u56fe\u5de5\u4f5c\u6d41\u540e\uff0c\u6211\u662f\u5982\u4f55\u653e\u5728\u4ea7\u54c1\u4e2d\u7528\u7684\uff1f<\/h3>\n\n\n\n
    1\u3001\u5bfc\u51fa\u5de5\u4f5c\u6d41\u4e3aAPI\u683c\u5f0f\u7684json\u6587\u4ef6<\/h4>\n\n\n
    \n
    \"\"<\/figure>\n<\/div>\n\n\n
    2\u3001\u67e5\u770b ComfyUI \u5b9e\u9645\u8fd0\u884c\u7aef\u53e3<\/h4>\n\n\n\n
    3\u3001\u7528\u672c\u673a\u5730\u5740\u9a8c\u8bc1 ComfyUI \u662f\u5426\u6b63\u5e38<\/h4>\n\n\n\n
    4\u3001\u5728\u5e73\u53f0\u9875\u9762\u6dfb\u52a0\u771f\u5b9e\u8fd0\u884c\u7aef\u53e3\u7684\u516c\u7f51\u6620\u5c04<\/h4>\n\n\n
    \n
    \"\"<\/figure>\n<\/div>\n\n
    \n
    \"\"<\/figure>\n<\/div>\n\n\n
    \u6211\u67e5\u5230\u7684\u7aef\u53e3\u662f7860\uff0c\u6dfb\u52a07860\u7aef\u53e3\uff0c\u628aURL\u5730\u5740\u590d\u5236\u7ed9AI\u5c31\u884c\u4e86\u3002\u540e\u9762\u5c31\u662f\u8ba9AI\u6839\u636eAPI.json\u7684\u683c\u5f0f\u5411\u8be5URL\u8bf7\u6c42\u56fe\u50cf\u751f\u6210\uff0c\u5e76\u4e14\u8fd4\u56de\u56fe\u50cf\u5230\u672c\u5730\uff0c\u663e\u793a\u5728\u4ea7\u54c1\u524d\u7aef\u3002<\/p>\n\n\n\n
    \u4e03\u3001ComfyUI \u5de5\u4f5c\u6d41\u548c\u57fa\u4e8e API JSON \u683c\u5f0f\u901a\u8fc7 URL \u8bf7\u6c42\u56fe\u50cf\u751f\u6210\u7684\u5b9e\u73b0\u539f\u7406\u4e0e\u533a\u522b<\/h3>\n\n\n\n
    \u5728 ComfyUI \u7f51\u9875\u7aef\u6d4b\u8bd5\u751f\u6210\u65f6\uff0c\u5728\u9875\u9762\u4e0a\u770b\u5230\u7684\u5de5\u4f5c\u6d41\u5176\u5b9e\u5c31\u662f\u4e00\u4e2a\u53ef\u89c6\u5316\u914d\u7f6e\u5668\u3002\u70b9\u201c\u8fd0\u884c\u201d\u540e\uff0c\u524d\u7aef\u4f1a\u628a\u5f53\u524d\u5de5\u4f5c\u6d41\u91cc\u7684\u8282\u70b9\u53c2\u6570\uff0c\u6bd4\u5982\u63d0\u793a\u8bcd\u3001\u5bbd\u5ea6\u3001\u9ad8\u5ea6\u3001seed\u3001steps\u3001\u6a21\u578b\u8282\u70b9\u8fde\u63a5\u5173\u7cfb\u7b49\uff0c\u63d0\u4ea4\u7ed9\u670d\u52a1\u5668\u7aef\u7684 ComfyUI \u540e\u7aef\uff1bComfyUI \u540e\u7aef\u518d\u6309\u8fd9\u4e2a\u5de5\u4f5c\u6d41\u53bb\u8c03\u7528 GPU \u4e0a\u7684 FLUX \u6a21\u578b\u5b8c\u6210\u63a8\u7406\u751f\u6210\u3002\u73b0\u5728\u7684 API \u6587\u4ef6\u91cc\u4e5f\u80fd\u770b\u5230\u8fd9\u4e9b\u8282\u70b9\u3002<\/p>\n\n\n\n
    \u800c\u5728\u672c\u5730\u4ee3\u7801\u6d4b\u8bd5\u65f6\uff0c\u672c\u8d28\u4e0a\u662f\u8df3\u8fc7\u4e86ComfyUI\u7684\u7f51\u9875\u754c\u9762\uff0c\u76f4\u63a5\u628a\u5bfc\u51fa\u7684 API.json \u5f53\u4f5c\u201c\u5de5\u4f5c\u6d41\u8bf7\u6c42\u4f53\u6a21\u677f\u201d\uff0c\u7531\u4ee3\u7801\u4fee\u6539\u91cc\u9762\u7684\u53c2\u6570\uff0c\u7136\u540e\u901a\u8fc7 URL \u8bf7\u6c42\u8fdc\u7a0b ComfyUI \u7684\u63a5\u53e3\uff0c\u4f8b\u5982 \/prompt\u3002ComfyUI \u6536\u5230\u8fd9\u4e2a JSON \u540e\uff0c\u6267\u884c\u7684\u8fd8\u662f\u540c\u4e00\u5957\u6a21\u578b\u63a8\u7406\u903b\u8f91\u3002<\/p>\n\n\n\n
    \u533a\u522b\u662f\uff1a\u7f51\u9875\u7aef\u662f\u201c\u53ef\u89c6\u5316\u754c\u9762\u5e2e\u4f60\u63d0\u4ea4\u5de5\u4f5c\u6d41\u201d\uff0c\u4ee3\u7801\u7aef\u662f\u201c\u4f60\u81ea\u5df1\u628a API \u5de5\u4f5c\u6d41 JSON \u63d0\u4ea4\u7ed9\u670d\u52a1\u5668\u201d\u3002<\/p>\n\n\n\n
    \u516b\u3001\u622a\u6b622026\/5\/15\uff0c\u4ea7\u54c1\u8c03\u7528Flux2\u6a21\u578b\u9047\u5230\u7684\u95ee\u9898\u3002\u4ee5\u53ca\u540e\u671f\u7684\u6a21\u578b\u5fae\u8c03\u3002<\/h3>\n\n\n\n
    \u95ee\u9898\uff1a\u4ea7\u54c1\u5728\u672c\u5730localhost\u6d4b\u8bd5\u6a21\u578bFlux2\u6a21\u578b\u5b8c\u5168\u6ca1\u95ee\u9898\u3002\u4f46\u662f\uff0c\u90e8\u7f72\u5230\u516c\u7f51\u540e\uff0c\u867d\u7136\u80fd\u591f\u6b63\u5e38\u751f\u6210\u56fe\u7247\uff0c\u4f46\u662f\u62ff\u4e0d\u56de\u56fe\u7247\u8fd4\u56de\u5230\u4ea7\u54c1\u524d\u7aef\u3002<\/p>\n\n\n\n
    \u6a21\u578b\u5fae\u8c03\u5206\u4e3a\u4e24\u7c7b\uff1a<\/p>\n\n\n\n
      \n
    • \u63a8\u7406\u53c2\u6570\u8c03\u4f18<\/li>\n\n\n\n
    • \u6a21\u578b\u8bad\u7ec3 \/ LoRA \u5fae\u8c03<\/li>\n<\/ul>\n\n\n\n
      \u7b2c\u4e00\u7c7b\uff0c\u63a8\u7406\u53c2\u6570\u8c03\u4f18\uff0c\u4e0d\u91cd\u65b0\u8bad\u7ec3\u6a21\u578b\uff0c\u53ea\u8c03\u6574\u751f\u6210\u8fc7\u7a0b\u91cc\u7684\u53c2\u6570\uff0c\u8ba9\u51fa\u56fe\u66f4\u7a33\u5b9a\u3001\u66f4\u7b26\u5408\u4ea7\u54c1\u9700\u6c42\u3002<\/p>\n\n\n\n
      \u7b2c\u4e8c\u7c7b,\u8fdb\u884c\u771f\u6b63\u7684\u5fae\u8c03\uff0c\u5927\u6982\u601d\u8def\uff1a<\/p>\n\n\n\n
        \n
      • \u6536\u96c6 30\uff5e50 \u5f20\u7edf\u4e00\u98ce\u683c\u6d3b\u52a8\u6d77\u62a5\uff0c\u6e05\u6d17\u6389\u4f4e\u8d28\u91cf\u548c\u6587\u5b57\u8fc7\u591a\u7684\u56fe<\/li>\n\n\n\n
      • \u6bcf\u5f20\u56fe\u5199\u82f1\u6587 caption\uff0c\u7edf\u4e00\u52a0\u89e6\u53d1\u8bcd fpoly poster style<\/li>\n\n\n\n
      • \u5148\u7528 512\/768 \u5206\u8fa8\u7387\u3001rank 4\/8\u3001500\uff5e1000 steps \u8dd1\u901a<\/li>\n\n\n\n
      • \u56fa\u5b9a 10 \u6761\u6d4b\u8bd5 prompt\uff0c\u5bf9\u6bd4\u539f\u6a21\u578b\u548c LoRA \u6a21\u578b<\/li>\n\n\n\n
      • \u628a LoRA \u52a0\u5165\u5de5\u4f5c\u6d41\uff0c\u8c03 LoRA \u6743\u91cd 0.6\u30010.8\u30011.0<\/li>\n\n\n\n
      • \u5bfc\u51fa ImageFlux_Poster_API.json\uff0c\u63a5\u5165\u4ea7\u54c1<\/li>\n\n\n\n
      • \u524d\u7aef\u589e\u52a0\u201c\u6d3b\u52a8\u6d77\u62a5\u201d\u98ce\u683c\u5165\u53e3\uff0c\u540e\u7aef\u81ea\u52a8\u4f7f\u7528\u6d77\u62a5 LoRA \u5de5\u4f5c\u6d41<\/li>\n<\/ul>\n\n\n\n
        \u4e5d\u3001\u95ee\u9898\u89e3\u51b3<\/h3>\n\n\n\n
        \u4e4b\u524d\u80fd\u751f\u6210\uff0c\u4f46\u662f\u524d\u7aef\u4e0d\u663e\u793a\u662f\u7531\u4e8eComfyUI \u4e91\u5b9e\u4f8b\u5230\u90e8\u7f72\u4ea7\u54c1\u7684\u670d\u52a1\u5668\u7684\u7f51\u7edc\u6781\u5dee\uff0c\u5373\u4f7f\u5728ComfyUI\u751f\u6210\u4e86\uff0c\u4f46\u662f\u4e0b\u8f7d\u5230\u670d\u52a1\u5668\u672c\u5730\u5f88\u6162\uff0c\u53ea\u6709\u4e0b\u8f7d\u6210\u529f\uff0c\u624d\u8fd4\u56de\u5230\u524d\u7aef\u663e\u793a\u3002\u7136\u540e\u6211\u6539\u4e86\u4e00\u4e2a\u7b56\u7565\uff0cComfyUI\u751f\u6210\u6210\u529f\uff0c\u7acb\u5373\u501f\u52a9\u751f\u6210\u56fe\u7247\u7684URL\u663e\u793a\u5728\u524d\u7aef\uff0c\u540e\u7aef\u9759\u9ed8\u4e0b\u8f7d\u56fe\u7247\u8fdb\u884c\u670d\u52a1\u5668\u672c\u5730\u5b58\u50a8\u3002<\/p>\n\n\n\n
        \u5341\u3001\u56fe\u751f\u56fe\u5de5\u4f5c\u6d41\u62d3\u5c55<\/h3>\n\n\n\n
        \u5728\u524d\u9762\u7684\u6587\u7ae0\u4e2d\uff0c\u6211\u4e3b\u8981\u8bb0\u5f55\u4e86 F-PolyImage \u4ea7\u54c1\u5982\u4f55\u901a\u8fc7\u4e91 GPU \u90e8\u7f72 FLUX.2 Klein \u6587\u751f\u56fe\u5de5\u4f5c\u6d41\uff0c\u5e76\u901a\u8fc7 ComfyUI \u7684 API JSON \u63a5\u5165\u4ea7\u54c1\u540e\u7aef\u3002\u540e\u7eed\u5b9e\u9a8c\u4e2d\uff0c\u6211\u7ee7\u7eed\u6d4b\u8bd5\u4e86 FLUX.2 Klein \u7684\u56fe\u751f\u56fe\u80fd\u529b\uff0c\u4e5f\u5c31\u662f\u57fa\u4e8e\u7528\u6237\u4e0a\u4f20\u7684\u53c2\u8003\u56fe\uff0c\u518d\u7ed3\u5408\u63d0\u793a\u8bcd\u751f\u6210\u65b0\u7684\u56fe\u7247\u3002<\/p>\n\n\n\n
        \u56fe\u751f\u56fe\u548c\u6587\u751f\u56fe\u7684\u5e95\u5c42\u903b\u8f91\u6709\u5f88\u591a\u76f8\u4f3c\u4e4b\u5904\uff1a\u4e8c\u8005\u90fd\u8fd0\u884c\u5728\u540c\u4e00\u4e2a\u4e91 GPU \u670d\u52a1\u5668\u4e0a\u7684 ComfyUI \u670d\u52a1\u4e2d\uff0c\u90fd\u901a\u8fc7 ComfyUI \u7684 \/prompt<\/code> \u63a5\u53e3\u63d0\u4ea4\u5de5\u4f5c\u6d41\u4efb\u52a1\uff0c\u4e5f\u90fd\u53ef\u4ee5\u901a\u8fc7 \/history<\/code> \u548c \/view<\/code> \u83b7\u53d6\u751f\u6210\u7ed3\u679c\u3002\u4e0d\u540c\u70b9\u5728\u4e8e\uff0c\u56fe\u751f\u56fe\u5728\u63d0\u4ea4\u4efb\u52a1\u4e4b\u524d\uff0c\u9700\u8981\u5148\u628a\u7528\u6237\u4e0a\u4f20\u7684\u56fe\u7247\u4f20\u5230 ComfyUI\uff0c\u7136\u540e\u5728 API JSON \u4e2d\u628a LoadImage<\/code> \u8282\u70b9\u7684\u56fe\u7247\u540d\u79f0\u66ff\u6362\u6210\u7528\u6237\u5b9e\u9645\u4e0a\u4f20\u7684\u6587\u4ef6\u540d\u3002<\/p>\n\n\n\n
        1\u3001\u4e0b\u8f7d\u5b98\u65b9\u56fe\u751f\u56fe\u5de5\u4f5c\u6d41<\/h4>\n\n\n\n
        \u6211\u5f53\u524d\u7684\u670d\u52a1\u5668\u7ec8\u7aef\u4f4d\u7f6e\u662f\uff1a<\/p>\n\n\n\n
        (base) root@instance:~#<\/code><\/pre>\n\n\n\n
        \u9996\u5148\u786e\u8ba4 ComfyUI \u662f\u5426\u5b58\u5728\uff1a<\/p>\n\n\n\n
        ls -lh \/root<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u770b\u5230\uff1a<\/p>\n\n\n\n
        ComfyUI<\/code><\/pre>\n\n\n\n
        \u8bf4\u660e ComfyUI \u76ee\u5f55\u5b58\u5728\u3002\u7136\u540e\u8fdb\u5165 ComfyUI \u76ee\u5f55\uff1a<\/p>\n\n\n\n
        cd \/root\/ComfyUI
        pwd<\/code><\/pre>\n\n\n\n
        \u6b63\u5e38\u8f93\u51fa\u5e94\u8be5\u662f\uff1a<\/p>\n\n\n\n
        \/root\/ComfyUI<\/code><\/pre>\n\n\n\n
        \u63a5\u7740\u521b\u5efa\u4e00\u4e2a\u4e13\u95e8\u5b58\u653e FLUX.2 Klein \u5de5\u4f5c\u6d41 JSON \u7684\u76ee\u5f55\uff1a<\/p>\n\n\n\n
        mkdir -p workflows\/flux2-klein<\/code><\/pre>\n\n\n\n
        \u4e0b\u8f7d\u5b98\u65b9\u56fe\u751f\u56fe \/ \u56fe\u50cf\u7f16\u8f91 Base \u5de5\u4f5c\u6d41\uff1a<\/p>\n\n\n\n
        curl -L -o workflows\/flux2-klein\/image_flux2_klein_image_edit_4b_base.json https:\/\/raw.githubusercontent.com\/Comfy-Org\/workflow_templates\/refs\/heads\/main\/templates\/image_flux2_klein_image_edit_4b_base.json<\/code><\/pre>\n\n\n\n
        \u518d\u4e0b\u8f7d Distilled \u5feb\u901f\u7248\u56fe\u751f\u56fe\u5de5\u4f5c\u6d41\uff1a<\/p>\n\n\n\n
        curl -L -o workflows\/flux2-klein\/image_flux2_klein_image_edit_4b_distilled.json https:\/\/raw.githubusercontent.com\/Comfy-Org\/workflow_templates\/refs\/heads\/main\/templates\/image_flux2_klein_image_edit_4b_distilled.json<\/code><\/pre>\n\n\n\n
        \u4e0b\u8f7d\u5b8c\u6210\u540e\u68c0\u67e5\uff1a<\/p>\n\n\n\n
        ls -lh workflows\/flux2-klein<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u770b\u5230\uff1a<\/p>\n\n\n\n
        image_flux2_klein_image_edit_4b_base.json
        image_flux2_klein_image_edit_4b_distilled.json<\/code><\/pre>\n\n\n\n
        \u8bf4\u660e\u5b98\u65b9\u56fe\u751f\u56fe\u5de5\u4f5c\u6d41\u5df2\u7ecf\u4e0b\u8f7d\u6210\u529f\u3002<\/p>\n\n\n\n
        2\u3001\u786e\u8ba4\u6a21\u578b\u6587\u4ef6\u662f\u5426\u9f50\u5168<\/h4>\n\n\n\n
        \u6211\u7684 ComfyUI \u6a21\u578b\u76ee\u5f55\u662f\u8f6f\u94fe\u63a5\u5230\u4e91\u76d8\u7684\uff1a<\/p>\n\n\n\n
        models\/diffusion_models -> \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models
        models\/text_encoders    -> \/root\/onethingai-fs\/mymodels\/flux2\/text_encoders
        models\/vae              -> \/root\/onethingai-fs\/mymodels\/flux2\/vae<\/code><\/pre>\n\n\n\n
        \u56e0\u6b64\u8981\u67e5\u770b\u771f\u5b9e\u6a21\u578b\u76ee\u5f55\u4e2d\u7684\u6587\u4ef6\uff1a<\/p>\n\n\n\n
        ls -lh \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models<\/code><\/pre>\n\n\n\n
        ls -lh \/root\/onethingai-fs\/mymodels\/flux2\/text_encoders<\/code><\/pre>\n\n\n\n
        ls -lh \/root\/onethingai-fs\/mymodels\/flux2\/vae<\/code><\/pre>\n\n\n\n
        \u56fe\u751f\u56fe\u5de5\u4f5c\u6d41\u4e3b\u8981\u9700\u8981\u8fd9\u4e9b\u6a21\u578b\u6587\u4ef6\uff1a<\/p>\n\n\n\n
        flux-2-klein-4b-fp8.safetensors
        qwen_3_4b.safetensors
        flux2-vae.safetensors<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u4f7f\u7528\u90e8\u5206 Base \u56fe\u50cf\u7f16\u8f91\u5de5\u4f5c\u6d41\uff0c\u53ef\u80fd\u8fd8\u9700\u8981\uff1a<\/p>\n\n\n\n
        flux-2-klein-base-4b-fp8.safetensors
        full_encoder_small_decoder.safetensors<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u7f3a\u5c11 Base \u4e3b\u6a21\u578b\uff0c\u53ef\u4ee5\u4e0b\u8f7d\uff1a<\/p>\n\n\n\n
        wget -c -O \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models\/flux-2-klein-base-4b-fp8.safetensors \"https:\/\/huggingface.co\/black-forest-labs\/FLUX.2-klein-base-4b-fp8\/resolve\/main\/flux-2-klein-base-4b-fp8.safetensors\"<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u7f3a\u5c11\u56fe\u50cf\u7f16\u8f91 VAE\uff0c\u53ef\u4ee5\u4e0b\u8f7d\uff1a<\/p>\n\n\n\n
        wget -c -O \/root\/onethingai-fs\/mymodels\/flux2\/vae\/full_encoder_small_decoder.safetensors \"https:\/\/huggingface.co\/black-forest-labs\/FLUX.2-small-decoder\/resolve\/main\/full_encoder_small_decoder.safetensors\"<\/code><\/pre>\n\n\n\n
        \u4e0b\u8f7d\u540e\u518d\u6b21\u68c0\u67e5\uff1a<\/p>\n\n\n\n
        ls -lh \/root\/onethingai-fs\/mymodels\/flux2\/vae<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u770b\u5230\uff1a<\/p>\n\n\n\n
        flux2-vae.safetensors
        full_encoder_small_decoder.safetensors<\/code><\/pre>\n\n\n\n
        \u8bf4\u660e VAE \u6587\u4ef6\u51c6\u5907\u5b8c\u6210\u3002<\/p>\n\n\n\n
        3\u3001\u628a\u56fe\u751f\u56fe\u5de5\u4f5c\u6d41 JSON \u4e0b\u8f7d\u5230\u672c\u5730\u7535\u8111<\/h4>\n\n\n\n
        ComfyUI \u7684\u5de5\u4f5c\u6d41 JSON \u6587\u4ef6\u867d\u7136\u5df2\u7ecf\u4e0b\u8f7d\u5230\u4e86\u670d\u52a1\u5668\u4e0a\uff0c\u4f46\u5982\u679c\u8981\u62d6\u5165\u6d4f\u89c8\u5668\u91cc\u7684 ComfyUI \u753b\u5e03\uff0c\u8fd8\u9700\u8981\u628a JSON \u6587\u4ef6\u4e0b\u8f7d\u5230\u672c\u5730\u7535\u8111\u3002<\/p>\n\n\n\n
        \u53ef\u4ee5\u5728\u670d\u52a1\u5668\u4e0a\u4e34\u65f6\u5f00\u542f\u4e00\u4e2a HTTP \u4e0b\u8f7d\u670d\u52a1\uff1a<\/p>\n\n\n\n
        cd \/root\/ComfyUI\/workflows\/flux2-klein
        python3 -m http.server 8899<\/code><\/pre>\n\n\n\n
        \u7ec8\u7aef\u51fa\u73b0\u7c7b\u4f3c\uff1a<\/p>\n\n\n\n
        Serving HTTP on 0.0.0.0 port 8899 ...<\/code><\/pre>\n\n\n\n
        \u8bf4\u660e\u4e34\u65f6\u6587\u4ef6\u670d\u52a1\u5df2\u7ecf\u542f\u52a8\u3002<\/p>\n\n\n\n
        \u7136\u540e\u5728\u672c\u5730\u6d4f\u89c8\u5668\u8bbf\u95ee\uff1a<\/p>\n\n\n\n
        http://\u4f60\u7684\u670d\u52a1\u5668\u516c\u7f51IP:8899\/<\/code><\/pre>\n\n\n\n
        \u5982\u679c 8899 \u7aef\u53e3\u6253\u4e0d\u5f00\uff0c\u8bf4\u660e\u8fd8\u6ca1\u6709\u505a\u516c\u7f51\u6620\u5c04\u3002\u53ef\u4ee5\u5230\u4e91 GPU \u5e73\u53f0\u7684\u5b9e\u4f8b\u63a7\u5236\u53f0\u4e2d\u6dfb\u52a0 8899 \u7aef\u53e3\u7684\u516c\u7f51\u6620\u5c04\u3002<\/p>\n\n\n\n
        \u8fdb\u5165\u9875\u9762\u540e\u4e0b\u8f7d\uff1a<\/p>\n\n\n\n
        image_flux2_klein_image_edit_4b_base.json
        image_flux2_klein_image_edit_4b_distilled.json<\/code><\/pre>\n\n\n\n
        \u4e0b\u8f7d\u5230\u672c\u5730\u7535\u8111\u540e\uff0c\u6253\u5f00 ComfyUI \u7f51\u9875\uff0c\u628a JSON \u6587\u4ef6\u76f4\u63a5\u62d6\u5230 ComfyUI \u753b\u5e03\u91cc\u5373\u53ef\u3002<\/p>\n\n\n\n
        4\u3001\u540e\u7eed\u63a5\u5165\u4ea7\u54c1\u540e\u7aef\u65f6\uff0c\u4f9d\u7136\u5bfc\u51fa\u4e3aAPI\u6587\u4ef6\uff0c\u7136\u540e\u57fa\u4e8eAPI\u6587\u4ef6\u7684\u683c\u5f0f\u8fdb\u884c\u4f20\u53c2\u751f\u56fe\u3002<\/h4>\n\n\n\n
        \u5341\u4e00\u3001\u622a\u81f32026\/5\/22\uff0c\u521d\u6b65\u5b8c\u6210\u5bf9lora\u5fae\u8c03\uff1a\u4ece 15 \u5f20\u7535\u8111\u7535\u5546\u6d77\u62a5\u5f00\u59cb\uff1a\u8bad\u7ec3\u4e00\u4e2a FLUX.2 Klein LoRA \u7684\u5b8c\u6574\u5b9e\u8df5\u8bb0\u5f55\u3002<\/h3>\n\n\n
        \n
        \"\"<\/figure>\n<\/div>\n\n\n
                                                             \uff08\u6d41\u7a0b\u56fe\uff09<\/p>\n\n\n\n
        \u6700\u8fd1\u6211\u5c1d\u8bd5\u7528\u81ea\u5df1\u7684\u7535\u8111\u7535\u5546\u6d77\u62a5\u6570\u636e\u96c6\uff0c\u8bad\u7ec3\u4e00\u4e2a\u53ef\u4ee5\u5728 ComfyUI \u5de5\u4f5c\u6d41\u4e2d\u4f7f\u7528\u7684 LoRA\u3002\u6574\u4e2a\u8fc7\u7a0b\u5e76\u4e0d\u662f\u7b80\u5355\u5730\u201c\u4e0a\u4f20\u56fe\u7247\u3001\u70b9\u8bad\u7ec3\u201d\u5c31\u7ed3\u675f\uff0c\u800c\u662f\u5b8c\u6574\u7ecf\u5386\u4e86\u6570\u636e\u96c6\u51c6\u5907\u3001\u8bad\u7ec3\u5668\u5b89\u88c5\u3001\u6a21\u578b\u8def\u5f84\u786e\u8ba4\u3001VAE \u9002\u914d\u3001LoRA \u6ce8\u5165\u4fee\u590d\u3001\u6b63\u5f0f\u8bad\u7ec3\u548c ComfyUI \u52a0\u8f7d\u6d4b\u8bd5\u3002<\/p>\n\n\n\n
        \u6700\u7ec8\uff0c\u6211\u6210\u529f\u8bad\u7ec3\u51fa\u4e86\u4e00\u4e2a\u9002\u7528\u4e8e FLUX.2 Klein 4B<\/strong> \u7684\u7535\u8111\u7535\u5546\u6d77\u62a5\u98ce\u683c LoRA\uff0c\u5e76\u5728 ComfyUI \u4e2d\u6210\u529f\u52a0\u8f7d\u51fa\u56fe\u3002<\/p>\n\n\n\n
        1\u3001\u6700\u7ec8\u76ee\u6807<\/h4>\n\n\n\n
        \u6211\u7684\u76ee\u6807\u5f88\u660e\u786e\uff1a
        \u7528 15 \u5f20\u7535\u8111\u7535\u5546\u6d77\u62a5\u56fe\uff0c\u8bad\u7ec3\u4e00\u4e2a LoRA\uff0c\u8ba9\u6a21\u578b\u5728\u751f\u6210\u56fe\u7247\u65f6\u66f4\u5bb9\u6613\u751f\u6210\u7c7b\u4f3c\u7684\u89c6\u89c9\u98ce\u683c\u3002<\/p>\n\n\n\n
        \u6211\u5e0c\u671b LoRA \u5b66\u5230\u7684\u4e0d\u662f\u5177\u4f53\u67d0\u4e00\u5f20\u56fe\uff0c\u800c\u662f\uff1a<\/p>\n\n\n\n
        \u7535\u8111\u4ea7\u54c1\u5c45\u4e2d\u5c55\u793a
        \u7535\u5546\u5e7f\u544a\u6d77\u62a5\u6784\u56fe
        \u79d1\u6280\u611f\u80cc\u666f
        \u9ad8\u5149\u3001\u5c4f\u5e55\u5149\u3001\u8fb9\u7f18\u5149
        \u5927\u6807\u9898\u533a\u57df
        \u5546\u4e1a\u4ea7\u54c1\u6444\u5f71\u6c1b\u56f4<\/code><\/pre>\n\n\n\n
        \u8bad\u7ec3\u5b8c\u6210\u540e\uff0c\u6211\u5e0c\u671b\u5728 ComfyUI \u7684 FLUX.2 Klein \u6587\u751f\u56fe\u5de5\u4f5c\u6d41\u4e2d\uff0c\u901a\u8fc7\u89e6\u53d1\u8bcd\u8c03\u7528\u8fd9\u4e2a\u98ce\u683c\u3002<\/p>\n\n\n\n
        \u6700\u7ec8\u4f7f\u7528\u7684\u89e6\u53d1\u8bcd\u662f\uff1a<\/p>\n\n\n\n
        fpoly_computer_poster_style<\/code><\/pre>\n\n\n\n
        2\u3001\u6574\u4f53\u8def\u7ebf\u9009\u62e9<\/h4>\n\n\n\n
        \u4e00\u5f00\u59cb\uff0c\u6211\u7684 ComfyUI \u5de5\u4f5c\u6d41\u4f7f\u7528\u7684\u662f\uff1a<\/p>\n\n\n\n
        flux-2-klein-4b-fp8.safetensors<\/code><\/pre>\n\n\n\n
        \u8fd9\u662f FLUX.2 Klein \u7684 fp8 \u63a8\u7406\u6a21\u578b\u3002<\/p>\n\n\n\n
        \u4f46 fp8 \u6a21\u578b\u66f4\u9002\u5408\u63a8\u7406\uff0c\u4e0d\u9002\u5408\u4f5c\u4e3a\u8bad\u7ec3\u5e95\u6a21\u3002\u56e0\u6b64\u8bad\u7ec3\u65f6\uff0c\u6211\u9009\u62e9\u4e86\u975e fp8 \u7248\u672c\uff1a<\/p>\n\n\n\n
        \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models\/flux-2-klein-4b.safetensors<\/code><\/pre>\n\n\n\n
        \u6700\u7ec8\u8def\u7ebf\u662f\uff1a<\/p>\n\n\n\n
        FLUX.2 Klein 4B \u975e fp8 \u6a21\u578b\u8bad\u7ec3 LoRA
        \u2193
        \u5bfc\u51fa LoRA
        \u2193
        \u590d\u5236\u5230 ComfyUI
        \u2193
        \u5728 FLUX.2 Klein fp8 \u5de5\u4f5c\u6d41\u4e2d\u52a0\u8f7d\u4f7f\u7528<\/code><\/pre>\n\n\n\n
        \u6ca1\u6709\u8d70 SDXL LoRA\uff0c\u4e5f\u6ca1\u6709\u8d70 FLUX.1-dev LoRA\uff0c\u800c\u662f\u76f4\u63a5\u6253\u901a\u4e86 FLUX.2 Klein 4B LoRA \u8bad\u7ec3\u8def\u7ebf<\/strong>\u3002<\/p>\n\n\n\n
        3\u3001\u8bad\u7ec3\u96c6\u51c6\u5907<\/h4>\n\n\n\n
        \u6211\u7684\u8bad\u7ec3\u96c6\u4e00\u5171\u6709 15 \u5f20\u56fe\u7247\uff0c\u6bcf\u5f20\u56fe\u7247\u90fd\u6709\u4e00\u4e2a\u5bf9\u5e94\u7684\u82f1\u6587\u63cf\u8ff0 txt\u3002<\/p>\n\n\n\n
        \u6700\u7ec8\u76ee\u5f55\u662f\uff1a<\/p>\n\n\n\n
        \/root\/ComfyUI\/input\/computer_poster_lora<\/code><\/pre>\n\n\n\n
        \u6587\u4ef6\u7ed3\u6784\u5982\u4e0b\uff1a<\/p>\n\n\n\n
        001.jpg
        001.txt
        002.jpg
        002.txt
        003.jpg
        003.txt
        ...
        015.jpg
        015.txt<\/code><\/pre>\n\n\n\n
        \u6bcf\u4e2a .txt<\/code> \u6587\u4ef6\u90fd\u4f7f\u7528\u540c\u4e00\u4e2a\u89e6\u53d1\u8bcd\u5f00\u5934\uff0c\u4f8b\u5982\uff1a<\/p>\n\n\n\n
        fpoly_computer_poster_style, computer e-commerce promotional poster, modern laptop computer, center composition with three-quarter front view, dark gradient background with subtle blue glow, dramatic rim lighting and screen glow, large text area at top, professional commercial advertising photography<\/code><\/pre>\n\n\n\n
        \u6211\u5148\u68c0\u67e5\u4e86\u6570\u636e\u96c6\u6570\u91cf\uff1a<\/p>\n\n\n\n
        cd \/root\/ComfyUI\/input\/computer_poster_lora

        echo \"\u56fe\u7247\u6570\u91cf\uff1a\"
        ls *.jpg *.png *.jpeg 2>\/dev\/null | wc -l

        echo \"txt\u6570\u91cf\uff1a\"
        ls *.txt 2>\/dev\/null | wc -l<\/code><\/pre>\n\n\n\n
        \u7ed3\u679c\u662f\uff1a<\/p>\n\n\n\n
        \u56fe\u7247\u6570\u91cf\uff1a15
        txt\u6570\u91cf\uff1a15<\/code><\/pre>\n\n\n\n
        \u7136\u540e\u68c0\u67e5\u89e6\u53d1\u8bcd\u662f\u5426\u7edf\u4e00\uff1a<\/p>\n\n\n\n
        grep -l \"^fpoly_computer_poster_style\" *.txt | wc -l
        grep -L \"^fpoly_computer_poster_style\" *.txt<\/code><\/pre>\n\n\n\n
        \u7ed3\u679c 15 \u4e2a txt \u90fd\u5305\u542b\u89e6\u53d1\u8bcd\uff0c\u6570\u636e\u96c6\u51c6\u5907\u5b8c\u6210\u3002<\/p>\n\n\n\n
        4\u3001\u8bad\u7ec3\u5de5\u5177\uff1aOstris AI Toolkit<\/h4>\n\n\n\n
        \u6211\u4f7f\u7528\u7684\u662f\uff1a<\/p>\n\n\n\n
        Ostris AI Toolkit<\/code><\/pre>\n\n\n\n
        \u5b89\u88c5\u8def\u5f84\uff1a<\/p>\n\n\n\n
        \/root\/ai-toolkit<\/code><\/pre>\n\n\n\n
        \u5b89\u88c5\u547d\u4ee4\uff1a<\/p>\n\n\n\n
        cd \/root
        git clone https:\/\/github.com\/ostris\/ai-toolkit.git
        cd \/root\/ai-toolkit
        pip install -r requirements.txt<\/code><\/pre>\n\n\n\n
        \u5b89\u88c5\u540e\u68c0\u67e5\uff1a<\/p>\n\n\n\n
        python run.py --help<\/code><\/pre>\n\n\n\n
        \u6b63\u5e38\u663e\u793a\u5e2e\u52a9\u4fe1\u606f\uff0c\u8bf4\u660e\u8bad\u7ec3\u5668\u53ef\u4ee5\u8fd0\u884c\u3002<\/p>\n\n\n\n
        5\u3001\u786c\u4ef6\u73af\u5883<\/h4>\n\n\n\n
        \u6211\u7684\u8bad\u7ec3\u73af\u5883\u662f\uff1a<\/p>\n\n\n\n
        GPU\uff1aNVIDIA GeForce RTX 4090
        \u663e\u5b58\uff1a23.53GB
        PyTorch\uff1a2.7.1+cu126
        CUDA\uff1a\u53ef\u7528<\/code><\/pre>\n\n\n\n
        \u68c0\u67e5\u547d\u4ee4\uff1a<\/p>\n\n\n\n
        python - <<'PY'
        import torch
        print(\"torch:\", torch.__version__)
        print(\"cuda available:\", torch.cuda.is_available())
        if torch.cuda.is_available():
            print(\"gpu:\", torch.cuda.get_device_name(0))
            print(\"vram GB:\", round(torch.cuda.get_device_properties(0).total_memory \/ 1024**3, 2))
        PY<\/code><\/pre>\n\n\n\n
        \u56e0\u4e3a\u662f 4090 24GB \u7ea7\u522b\u663e\u5b58\uff0c\u6240\u4ee5\u8bad\u7ec3\u53c2\u6570\u91c7\u7528\u4fdd\u5b88\u65b9\u6848\uff1a<\/p>\n\n\n\n
        batch_size: 1
        LoRA rank: 16
        learning rate: 8e-5
        dtype: bf16
        quantize: true
        low_vram: true<\/code><\/pre>\n\n\n\n
        6\u3001\u786e\u8ba4 FLUX.2 Klein \u6a21\u578b\u6587\u4ef6<\/h4>\n\n\n\n
        \u6211\u5148\u67e5\u627e\u4e86\u672c\u5730\u6a21\u578b\uff1a<\/p>\n\n\n\n
        find \/root\/ComfyUI\/models \/root\/onethingai-fs\/mymodels -iname \"*flux*klein*\" -o -iname \"*flux-2*\"<\/code><\/pre>\n\n\n\n
        \u786e\u8ba4\u5b58\u5728\u8fd9\u4e9b\u6587\u4ef6\uff1a<\/p>\n\n\n\n
        \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models\/flux-2-klein-4b.safetensors
        \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models\/flux-2-klein-4b-fp8.safetensors
        \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models\/flux-2-klein-base-4b-fp8.safetensors<\/code><\/pre>\n\n\n\n
        \u6700\u7ec8\u8bad\u7ec3\u4f7f\u7528\uff1a<\/p>\n\n\n\n
        \/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models\/flux-2-klein-4b.safetensors<\/code><\/pre>\n\n\n\n
        ComfyUI \u63a8\u7406\u5de5\u4f5c\u6d41\u7ee7\u7eed\u4f7f\u7528\uff1a<\/p>\n\n\n\n
        flux-2-klein-4b-fp8.safetensors<\/code><\/pre>\n\n\n\n
        7\u3001\u8bad\u7ec3\u914d\u7f6e\u6587\u4ef6<\/h4>\n\n\n\n
        \u6211\u5148\u590d\u5236\u4e86 ai-toolkit \u7684 FLUX LoRA \u6a21\u677f\uff1a<\/p>\n\n\n\n
        cd \/root\/ai-toolkit
        cp config\/examples\/train_lora_flux_24gb.yaml config\/computer_poster_lora.yaml<\/code><\/pre>\n\n\n\n
        \u4e4b\u540e\u9010\u6b65\u4fee\u6539\u914d\u7f6e\u3002<\/p>\n\n\n\n
        \u6700\u7ec8\u5173\u952e\u914d\u7f6e\u5982\u4e0b\uff1a<\/p>\n\n\n\n
        name: \"computer_poster_lora_flux2_klein_test\"

        trigger_word: \"fpoly_computer_poster_style\"

        network:
          type: \"lora\"
          linear: 16
          linear_alpha: 16
          network_kwargs:
            target_lin_modules:
              - \"Flux2\"

        datasets:
          - folder_path: \"\/root\/ComfyUI\/input\/computer_poster_lora\"
            caption_ext: \"txt\"
            caption_dropout_rate: 0.05
            resolution: [512, 768, 1024]

        train:
          batch_size: 1
          steps: 600
          gradient_accumulation_steps: 1
          train_unet: true
          train_text_encoder: false
          gradient_checkpointing: true
          noise_scheduler: \"flowmatch\"
          optimizer: \"adamw8bit\"
          lr: 8e-5
          dtype: bf16
          disable_sampling: true

        model:
          name_or_path: \"\/root\/onethingai-fs\/mymodels\/flux2\/diffusion_models\/flux-2-klein-4b.safetensors\"
          arch: \"flux2_klein_4b\"
          quantize: true
          flux2_klein_te_path: \"\/root\/onethingai-fs\/mymodels\/flux2_test\/text_encoder\"
          vae_path: \"\/root\/onethingai-fs\/mymodels\/flux2\/vae\/full_encoder_small_decoder.safetensors\"
          low_vram: true<\/code><\/pre>\n\n\n\n
        \u5176\u4e2d\u6700\u5173\u952e\u7684\u4e09\u70b9\u662f\uff1a<\/p>\n\n\n\n
        arch: \"flux2_klein_4b\"<\/code><\/pre>\n\n\n\n
        network_kwargs:
          target_lin_modules:
            - \"Flux2\"<\/code><\/pre>\n\n\n\n
        vae_path: \"\/root\/onethingai-fs\/mymodels\/flux2\/vae\/full_encoder_small_decoder.safetensors\"<\/code><\/pre>\n\n\n\n
        8\u3001\u8e29\u5751\u4e00\uff1aVAE \u4e0d\u5339\u914d<\/h4>\n\n\n\n
        \u7b2c\u4e00\u6b21\u6d4b\u8bd5\u8bad\u7ec3\u65f6\uff0c\u6a21\u578b\u4e3b\u4f53\u548c Qwen3 \u6587\u672c\u7f16\u7801\u5668\u90fd\u52a0\u8f7d\u6210\u529f\u4e86\uff0c\u4f46 VAE \u62a5\u9519\uff1a<\/p>\n\n\n\n
        KeyError: 'decoder.up.0.block.0.conv1.bias'<\/code><\/pre>\n\n\n\n
        \u6700\u5f00\u59cb\u6211\u5c1d\u8bd5\u8fc7\uff1a<\/p>\n\n\n\n
        \/root\/onethingai-fs\/mymodels\/flux2_test\/vae\/diffusion_pytorch_model.safetensors<\/code><\/pre>\n\n\n\n
        \u4ee5\u53ca\uff1a<\/p>\n\n\n\n
        \/root\/onethingai-fs\/mymodels\/flux2\/vae\/flux2-vae.safetensors<\/code><\/pre>\n\n\n\n
        \u90fd\u5931\u8d25\u4e86\u3002<\/p>\n\n\n\n
        \u4e8e\u662f\u6211\u68c0\u67e5\u4e86\u51e0\u4e2a VAE \u6587\u4ef6\u7684 key\uff1a<\/p>\n\n\n\n
        python - <<'PY'
        from safetensors.torch import safe_open

        vae_files = [
            \"\/root\/onethingai-fs\/mymodels\/flux2\/vae\/flux2-vae.safetensors\",
            \"\/root\/onethingai-fs\/mymodels\/flux2\/vae\/full_encoder_small_decoder.safetensors\",
            \"\/root\/onethingai-fs\/mymodels\/flux2_test\/vae\/diffusion_pytorch_model.safetensors\",
        ]

        for path in vae_files:
            print(\"\\n===\", path, \"===\")
            with safe_open(path, framework=\"pt\", device=\"cpu\") as f:
                keys = list(f.keys())
                target = \"decoder.up.0.block.0.conv1.bias\"
                print(\"has target key:\", target in keys)
        PY<\/code><\/pre>\n\n\n\n
        \u7ed3\u679c\u53ea\u6709\u8fd9\u4e2a\u6587\u4ef6\u5305\u542b\u76ee\u6807 key\uff1a<\/p>\n\n\n\n
        \/root\/onethingai-fs\/mymodels\/flux2\/vae\/full_encoder_small_decoder.safetensors<\/code><\/pre>\n\n\n\n
        \u6240\u4ee5\u6700\u7ec8\u4f7f\u7528\u5b83\u4f5c\u4e3a VAE\u3002<\/p>\n\n\n\n
        \u8fd9\u4e2a\u95ee\u9898\u89e3\u51b3\u540e\uff0c\u65e5\u5fd7\u6210\u529f\u8d70\u5230\uff1a<\/p>\n\n\n\n
        Model Loaded<\/code><\/pre>\n\n\n\n
        9\u3001\u8e29\u5751\u4e8c\uff1aLoRA \u6ca1\u6709\u6302\u8f7d\u5230\u6a21\u578b<\/h4>\n\n\n\n
        \u89e3\u51b3 VAE \u540e\uff0c\u53c8\u9047\u5230\u65b0\u7684\u95ee\u9898\uff1a<\/p>\n\n\n\n
        create LoRA for U-Net: 0 modules.
        There are not any lora modules in this network.<\/code><\/pre>\n\n\n\n
        \u8fd9\u8bf4\u660e\u6a21\u578b\u52a0\u8f7d\u6210\u529f\u4e86\uff0c\u4f46 LoRA \u6ca1\u6709\u6302\u8f7d\u5230\u4efb\u4f55\u6a21\u5757\u3002<\/p>\n\n\n\n
        \u6211\u7ee7\u7eed\u67e5\u770b ai-toolkit \u7684\u4ee3\u7801\uff0c\u53d1\u73b0 FLUX.2 \u7684\u76ee\u6807\u6a21\u5757\u662f\uff1a<\/p>\n\n\n\n
        Flux2<\/code><\/pre>\n\n\n\n
        \u4e8e\u662f\u914d\u7f6e\u91cc\u52a0\u5165\uff1a<\/p>\n\n\n\n
        network_kwargs:
          target_lin_modules:
            - \"Flux2\"<\/code><\/pre>\n\n\n\n
        \u4f46\u7b2c\u4e00\u6b21\u52a0\u5165\u540e\u4ecd\u7136\u5931\u8d25\u3002\u539f\u56e0\u662f\u914d\u7f6e\u91cc\u8fd8\u4fdd\u7559\u4e86\uff1a<\/p>\n\n\n\n
        is_flux: true<\/code><\/pre>\n\n\n\n
        \u8fd9\u4f1a\u8ba9 ai-toolkit \u628a\u76ee\u6807\u6a21\u5757\u5f3a\u5236\u8986\u76d6\u6210 FLUX.1 \u7684\uff1a<\/p>\n\n\n\n
        FluxTransformer2DModel<\/code><\/pre>\n\n\n\n
        \u800c FLUX.2 Klein \u4e0d\u662f\u8fd9\u4e2a\u6a21\u5757\u540d\uff0c\u6240\u4ee5 LoRA \u4ecd\u7136\u6302\u4e0d\u4e0a\u3002<\/p>\n\n\n\n
        \u6700\u7ec8\u89e3\u51b3\u65b9\u6848\u662f\uff1a<\/p>\n\n\n\n
        \u5220\u9664 is_flux: true
        \u4fdd\u7559 arch: \"flux2_klein_4b\"
        \u624b\u52a8\u6307\u5b9a target_lin_modules: [\"Flux2\"]<\/code><\/pre>\n\n\n\n
        \u4fee\u590d\u540e\uff0c\u65e5\u5fd7\u663e\u793a\uff1a<\/p>\n\n\n\n
        create LoRA for U-Net: 80 modules.<\/code><\/pre>\n\n\n\n
        \u8fd9\u8bf4\u660e LoRA \u6210\u529f\u6302\u8f7d\u3002<\/p>\n\n\n\n
        10\u3001\u5148\u505a 20 \u6b65\u6d4b\u8bd5\u8bad\u7ec3<\/h4>\n\n\n\n
        \u6b63\u5f0f\u8bad\u7ec3\u524d\uff0c\u6211\u5148\u628a\u6b65\u6570\u8bbe\u4e3a\uff1a<\/p>\n\n\n\n
        steps: 20<\/code><\/pre>\n\n\n\n
        \u6d4b\u8bd5\u8bad\u7ec3\u6210\u529f\u540e\uff0c\u65e5\u5fd7\u4e2d\u51fa\u73b0\uff1a<\/p>\n\n\n\n
        create LoRA for U-Net: 80 modules.
        Found 15 images
        Caching latents to disk
        Saved checkpoint<\/code><\/pre>\n\n\n\n
        \u8fd9\u8bf4\u660e\u8bad\u7ec3\u94fe\u8def\u5df2\u7ecf\u6253\u901a\uff1a<\/p>\n\n\n\n
        \u6a21\u578b\u80fd\u52a0\u8f7d
        Qwen3 \u80fd\u52a0\u8f7d
        VAE \u80fd\u52a0\u8f7d
        LoRA \u80fd\u6302\u8f7d
        \u8bad\u7ec3\u96c6\u80fd\u8bfb\u53d6
        \u8bad\u7ec3\u80fd\u8dd1
        \u6743\u91cd\u80fd\u4fdd\u5b58<\/code><\/pre>\n\n\n\n
        11\u3001\u6b63\u5f0f\u8bad\u7ec3 600 \u6b65<\/h4>\n\n\n\n
        \u6d4b\u8bd5\u6210\u529f\u540e\uff0c\u6211\u628a\u6b65\u6570\u6539\u6210\uff1a<\/p>\n\n\n\n
        steps: 600<\/code><\/pre>\n\n\n\n
        \u6b63\u5f0f\u8bad\u7ec3\u547d\u4ee4\uff1a<\/p>\n\n\n\n
        cd \/root\/ai-toolkit
        python run.py config\/computer_poster_lora.yaml<\/code><\/pre>\n\n\n\n
        \u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u4fdd\u5b58\u4e86\u4e2d\u95f4\u7248\u672c\uff1a<\/p>\n\n\n\n
        computer_poster_lora_flux2_klein_test_000000250.safetensors
        computer_poster_lora_flux2_klein_test_000000500.safetensors<\/code><\/pre>\n\n\n\n
        \u6700\u7ec8\u4fdd\u5b58\uff1a<\/p>\n\n\n\n
        \/root\/ai-toolkit\/output\/computer_poster_lora_flux2_klein_test\/computer_poster_lora_flux2_klein_test.safetensors<\/code><\/pre>\n\n\n\n
        \u65e5\u5fd7\u4e2d\u5173\u952e\u7ed3\u679c\u662f\uff1a<\/p>\n\n\n\n
        Saved checkpoint to output\/computer_poster_lora_flux2_klein_test\/computer_poster_lora_flux2_klein_test.safetensors<\/code><\/pre>\n\n\n\n
        \u8bf4\u660e\u6b63\u5f0f\u8bad\u7ec3\u6210\u529f\u3002<\/p>\n\n\n\n
        12\u3001\u590d\u5236 LoRA \u5230 ComfyUI<\/h4>\n\n\n\n
        \u8bad\u7ec3\u5b8c\u6210\u540e\uff0c\u6211\u628a\u6700\u7ec8 LoRA \u590d\u5236\u5230 ComfyUI \u7684 LoRA \u76ee\u5f55\uff1a<\/p>\n\n\n\n
        mkdir -p \/root\/ComfyUI\/models\/loras

        cp \/root\/ai-toolkit\/output\/computer_poster_lora_flux2_klein_test\/computer_poster_lora_flux2_klein_test.safetensors \\
        \/root\/ComfyUI\/models\/loras\/computer_poster_lora_flux2_klein_v1.safetensors<\/code><\/pre>\n\n\n\n
        \u6700\u7ec8 LoRA \u6587\u4ef6\uff1a<\/p>\n\n\n\n
        \/root\/ComfyUI\/models\/loras\/computer_poster_lora_flux2_klein_v1.safetensors<\/code><\/pre>\n\n\n\n
        13\u3001ComfyUI \u5de5\u4f5c\u6d41\u63a5\u7ebf<\/h4>\n\n\n\n
        \u5728 ComfyUI \u91cc\uff0c\u6211\u6dfb\u52a0\u4e86\uff1a<\/p>\n\n\n\n
        LoRA \u52a0\u8f7d\u5668\uff08\u4ec5\u6a21\u578b\uff09
        Lora LoaderModelOnly<\/code><\/pre>\n\n\n\n
        \u56e0\u4e3a\u6211\u6ca1\u6709\u8bad\u7ec3\u6587\u672c\u7f16\u7801\u5668\uff0c\u6240\u4ee5\u53ea\u9700\u8981\u6a21\u578b\u7248 LoRA \u52a0\u8f7d\u5668\u3002<\/p>\n\n\n\n
        \u6700\u7ec8\u63a5\u7ebf\u662f\uff1a<\/p>\n\n\n\n
        UNet\u52a0\u8f7d\u5668
        \u2193
        LoRA\u52a0\u8f7d\u5668\uff08\u4ec5\u6a21\u578b\uff09
        \u2193
        CFG\u5f15\u5bfc\u5668
        \u2193
        \u91c7\u6837\u5668
        \u2193
        VAE\u89e3\u7801
        \u2193
        \u4fdd\u5b58\u56fe\u7247<\/code><\/pre>\n\n\n\n
        \u4e5f\u5c31\u662f\u628a LoRA \u63d2\u5728\uff1a<\/p>\n\n\n\n
        UNet\u52a0\u8f7d\u5668 \u548c CFG\u5f15\u5bfc\u5668 \u4e4b\u95f4<\/code><\/pre>\n\n\n\n
        LoRA \u5f3a\u5ea6\u521d\u59cb\u8bbe\u7f6e\u4e3a\uff1a<\/p>\n\n\n\n
        0.70<\/code><\/pre>\n\n\n\n
        \"\"<\/figure>\n\n\n\n
        14\u3001\u63d0\u793a\u8bcd\u6d4b\u8bd5<\/h4>\n\n\n\n
        \u6d4b\u8bd5\u65f6\u63d0\u793a\u8bcd\u5fc5\u987b\u5305\u542b\u89e6\u53d1\u8bcd\uff1a<\/p>\n\n\n\n
        fpoly_computer_poster_style<\/code><\/pre>\n\n\n\n
        \u4f8b\u5982\uff1a<\/p>\n\n\n\n
        fpoly_computer_poster_style, modern laptop e-commerce promotional poster, product centered, dark blue technology background, dramatic rim lighting, glowing screen, clean premium commercial layout, large headline area, professional product advertising design<\/code><\/pre>\n\n\n\n
        \u6700\u7ec8 ComfyUI \u6210\u529f\u51fa\u56fe\uff0c\u753b\u9762\u5df2\u7ecf\u6709\u660e\u663e\u7684\u7535\u8111\u7535\u5546\u6d77\u62a5\u98ce\u683c\u3002<\/p>\n\n\n\n
        15\u3001\u6700\u7ec8\u6210\u679c<\/h4>\n\n\n\n
        \u6700\u7ec8\u6211\u5f97\u5230\u7684 LoRA \u6587\u4ef6\u662f\uff1a<\/p>\n\n\n\n
        computer_poster_lora_flux2_klein_v1.safetensors<\/code><\/pre>\n\n\n\n
        \u5b83\u53ef\u4ee5\u5728\u6211\u7684 FLUX.2 Klein \u6587\u751f\u56fe\u5de5\u4f5c\u6d41\u4e2d\u4f7f\u7528\uff0c\u7528\u6765\u751f\u6210\u7535\u8111\u7535\u5546\u5e7f\u544a\u6d77\u62a5\u98ce\u683c\u56fe\u7247\u3002<\/p>\n\n\n\n
        \u8fd9\u6b21\u5b8c\u6574\u5b8c\u6210\u4e86\uff1a<\/p>\n\n\n\n
        \u8bad\u7ec3\u96c6\u51c6\u5907
        \u89e6\u53d1\u8bcd\u8bbe\u8ba1
        ai-toolkit \u5b89\u88c5
        FLUX.2 Klein \u6a21\u578b\u9002\u914d
        VAE \u4fee\u590d
        LoRA target \u4fee\u590d
        20 \u6b65\u6d4b\u8bd5\u8bad\u7ec3
        600 \u6b65\u6b63\u5f0f\u8bad\u7ec3
        ComfyUI \u52a0\u8f7d LoRA
        \u6210\u529f\u51fa\u56fe<\/code><\/pre>\n\n\n\n
        17\u3001\u540e\u7eed\u4f18\u5316\u65b9\u5411<\/h4>\n\n\n\n
        \u8fd9\u6b21\u8bad\u7ec3\u53ea\u7528\u4e86 15 \u5f20\u56fe\uff0c\u5df2\u7ecf\u80fd\u770b\u5230\u98ce\u683c\u6548\u679c\u3002\u540e\u7eed\u53ef\u4ee5\u7ee7\u7eed\u4f18\u5316\u3002<\/p>\n\n\n\n
        \u5982\u679c\u98ce\u683c\u4e0d\u591f\u660e\u663e\uff0c\u53ef\u4ee5\u5c1d\u8bd5\uff1a<\/p>\n\n\n\n
        LoRA \u5f3a\u5ea6\u63d0\u9ad8\u5230 0.8 - 1.0<\/code><\/pre>\n\n\n\n
        \u6216\u8005\u7ee7\u7eed\u8bad\u7ec3\u5230\uff1a<\/p>\n\n\n\n
        800 - 1000 steps<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u753b\u9762\u53d8\u5f62\u3001\u8fc7\u62df\u5408\u6216\u8005\u7535\u8111\u7ed3\u6784\u4e0d\u7a33\u5b9a\uff0c\u53ef\u4ee5\u964d\u4f4e LoRA \u5f3a\u5ea6\uff1a<\/p>\n\n\n\n
        0.45 - 0.6<\/code><\/pre>\n\n\n\n
        \u4e5f\u53ef\u4ee5\u6d4b\u8bd5\u4e2d\u95f4\u7248\u672c\uff1a<\/p>\n\n\n\n
        computer_poster_lora_flux2_klein_test_000000500.safetensors<\/code><\/pre>\n\n\n\n
        \u6709\u65f6 500 \u6b65\u6bd4\u6700\u7ec8 600 \u6b65\u66f4\u81ea\u7136\u3002<\/p>\n\n\n\n
        \u53e6\u5916\uff0cLoRA \u4e0d\u9002\u5408\u7cbe\u51c6\u751f\u6210\u6d77\u62a5\u6587\u5b57\u3002
        \u5b83\u66f4\u9002\u5408\u5b66\u4e60\u6784\u56fe\u3001\u98ce\u683c\u3001\u5149\u5f71\u548c\u5546\u4e1a\u8bbe\u8ba1\u6c1b\u56f4\u3002\u6d77\u62a5\u4e2d\u6587\u5b57\u6700\u597d\u540e\u671f\u7528\u8bbe\u8ba1\u8f6f\u4ef6\u3001\u5c40\u90e8\u91cd\u7ed8\u6216\u4e13\u95e8\u7684\u6587\u5b57\u63a7\u5236\u6d41\u7a0b\u5904\u7406\u3002<\/p>\n\n\n\n
        \u5341\u4e8c\u3001\u540e\u7eed\u6269\u5c55\uff1a\u5982\u679c\u8bad\u7ec3\u96c6\u589e\u52a0\u5230 1000 \u5f20\uff0c\u5982\u4f55\u5feb\u901f\u91cd\u65b0\u8bad\u7ec3\uff1f<\/h3>\n\n\n\n
        1. \u65b0\u5efa 1000 \u5f20\u8bad\u7ec3\u96c6\u76ee\u5f55<\/h4>\n\n\n\n
        \u6211\u5efa\u8bae\u4e0d\u8981\u8986\u76d6\u539f\u6765\u7684 15 \u5f20\u5c0f\u6570\u636e\u96c6\uff0c\u800c\u662f\u65b0\u5efa\u4e00\u4e2a\u76ee\u5f55\uff1a<\/p>\n\n\n\n
        mkdir -p \/root\/ComfyUI\/input\/computer_poster_lora_1000<\/code><\/pre>\n\n\n\n
        \u7136\u540e\u628a 1000 \u5f20\u56fe\u7247\u548c 1000 \u4e2a\u540c\u540d txt \u653e\u8fdb\u53bb\uff0c\u7ed3\u6784\u4ecd\u7136\u4fdd\u6301\uff1a<\/p>\n\n\n\n
        0001.jpg
        0001.txt
        0002.jpg
        0002.txt
        ...
        1000.jpg
        1000.txt<\/code><\/pre>\n\n\n\n
        \u6bcf\u4e2a txt \u4ecd\u7136\u5efa\u8bae\u4fdd\u7559\u540c\u4e00\u4e2a\u89e6\u53d1\u8bcd\uff1a<\/p>\n\n\n\n
        fpoly_computer_poster_style<\/code><\/pre>\n\n\n\n
        \u4f8b\u5982\uff1a<\/p>\n\n\n\n
        fpoly_computer_poster_style, modern laptop e-commerce promotional poster, product centered, premium technology background, dramatic commercial lighting, clean advertising layout<\/code><\/pre>\n\n\n\n
        2. \u68c0\u67e5\u6570\u636e\u6570\u91cf<\/h4>\n\n\n\n
        \u4e0a\u4f20\u5b8c\u6210\u540e\uff0c\u5148\u68c0\u67e5\u56fe\u7247\u548c txt \u6570\u91cf\uff1a<\/p>\n\n\n\n
        cd \/root\/ComfyUI\/input\/computer_poster_lora_1000

        echo \"\u56fe\u7247\u6570\u91cf\uff1a\"
        ls *.jpg *.png *.jpeg 2>\/dev\/null | wc -l

        echo \"txt\u6570\u91cf\uff1a\"
        ls *.txt 2>\/dev\/null | wc -l<\/code><\/pre>\n\n\n\n
        \u7406\u60f3\u7ed3\u679c\uff1a<\/p>\n\n\n\n
        \u56fe\u7247\u6570\u91cf\uff1a
        1000
        txt\u6570\u91cf\uff1a
        1000<\/code><\/pre>\n\n\n\n
        \u518d\u68c0\u67e5\u89e6\u53d1\u8bcd\uff1a<\/p>\n\n\n\n
        echo \"\u5305\u542b\u89e6\u53d1\u8bcd\u7684 txt \u6570\u91cf\uff1a\"
        grep -l \"^fpoly_computer_poster_style\" *.txt | wc -l

        echo \"\u6ca1\u6709\u89e6\u53d1\u8bcd\u7684 txt\uff1a\"
        grep -L \"^fpoly_computer_poster_style\" *.txt<\/code><\/pre>\n\n\n\n
        \u7406\u60f3\u7ed3\u679c\u662f\uff1a<\/p>\n\n\n\n
        \u5305\u542b\u89e6\u53d1\u8bcd\u7684 txt \u6570\u91cf\uff1a
        1000
        \u6ca1\u6709\u89e6\u53d1\u8bcd\u7684 txt\uff1a<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u7b2c\u4e8c\u90e8\u5206\u6ca1\u6709\u6587\u4ef6\u540d\u8f93\u51fa\uff0c\u5c31\u8bf4\u660e\u89e6\u53d1\u8bcd\u7edf\u4e00\u3002<\/p>\n\n\n\n
        3. \u590d\u5236\u4e00\u4efd\u65b0\u7684\u8bad\u7ec3\u914d\u7f6e<\/h4>\n\n\n\n
        \u4e0d\u8981\u76f4\u63a5\u8986\u76d6\u4e4b\u524d\u7684 15 \u5f20\u56fe\u8bad\u7ec3\u914d\u7f6e\uff0c\u53ef\u4ee5\u590d\u5236\u4e00\u4efd\u65b0\u914d\u7f6e\uff1a<\/p>\n\n\n\n
        cd \/root\/ai-toolkit

        cp config\/computer_poster_lora.yaml config\/computer_poster_lora_1000.yaml<\/code><\/pre>\n\n\n\n
        \u7136\u540e\u4fee\u6539\u914d\u7f6e\u91cc\u7684\u540d\u5b57\u3001\u6570\u636e\u96c6\u8def\u5f84\u548c\u8bad\u7ec3\u6b65\u6570\uff1a<\/p>\n\n\n\n
        sed -i 's|computer_poster_lora_flux2_klein_test|computer_poster_lora_flux2_klein_1000_v1|g' config\/computer_poster_lora_1000.yaml

        sed -i 's|\/root\/ComfyUI\/input\/computer_poster_lora|\/root\/ComfyUI\/input\/computer_poster_lora_1000|g' config\/computer_poster_lora_1000.yaml<\/code><\/pre>\n\n\n\n
        4. 1000 \u5f20\u56fe\u5efa\u8bae\u8bad\u7ec3\u591a\u5c11\u6b65\uff1f<\/h4>\n\n\n\n
        \u5982\u679c\u8fd8\u662f\u8bad\u7ec3\u201c\u98ce\u683c\u7c7b LoRA\u201d\uff0c1000 \u5f20\u6570\u636e\u4e0d\u5efa\u8bae\u53ea\u8dd1 600 \u6b65\u3002<\/p>\n\n\n\n
        \u53ef\u4ee5\u5148\u4ece\uff1a<\/p>\n\n\n\n
        steps: 3000<\/code><\/pre>\n\n\n\n
        \u5f00\u59cb\u6d4b\u8bd5\u3002<\/p>\n\n\n\n
        \u4fee\u6539\u547d\u4ee4\uff1a<\/p>\n\n\n\n
        sed -i 's|steps: 600|steps: 3000|g' config\/computer_poster_lora_1000.yaml<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u539f\u914d\u7f6e\u91cc\u8fd8\u662f steps: 20<\/code>\uff0c\u5219\u8fd0\u884c\uff1a<\/p>\n\n\n\n
        sed -i 's|steps: 20|steps: 3000|g' config\/computer_poster_lora_1000.yaml<\/code><\/pre>\n\n\n\n
        \u4e5f\u53ef\u4ee5\u66f4\u7a33\u59a5\u5730\u624b\u52a8\u68c0\u67e5\uff1a<\/p>\n\n\n\n
        grep -E 'name:|folder_path:|steps:|lr:|linear:|linear_alpha:|arch:|target_lin_modules:|vae_path:' config\/computer_poster_lora_1000.yaml<\/code><\/pre>\n\n\n\n
        \u6211\u5efa\u8bae 1000 \u5f20\u56fe\u7b2c\u4e00\u7248\u4fdd\u6301\u8fd9\u4e9b\u53c2\u6570\u4e0d\u53d8\uff1a<\/p>\n\n\n\n
        linear: 16
        linear_alpha: 16
        lr: 8e-5
        batch_size: 1
        train_text_encoder: false
        arch: \"flux2_klein_4b\"
        target_lin_modules:
          - \"Flux2\"<\/code><\/pre>\n\n\n\n
        \u5148\u4e0d\u8981\u4e00\u4e0a\u6765\u6539 rank\u3001\u5b66\u4e60\u7387\u548c text encoder\u3002\u6570\u636e\u91cf\u53d8\u5927\u540e\uff0c\u5148\u9a8c\u8bc1\u7a33\u5b9a\u6027\u66f4\u91cd\u8981\u3002<\/p>\n\n\n\n
        5. \u91cd\u65b0\u8bad\u7ec3\u547d\u4ee4<\/h4>\n\n\n\n
        \u6b63\u5f0f\u91cd\u65b0\u8bad\u7ec3\u53ea\u9700\u8981\u8fd0\u884c\uff1a<\/p>\n\n\n\n
        cd \/root\/ai-toolkit
        python run.py config\/computer_poster_lora_1000.yaml<\/code><\/pre>\n\n\n\n
        \u8bad\u7ec3\u5b8c\u6210\u540e\uff0c\u8f93\u51fa\u76ee\u5f55\u4f1a\u53d8\u6210\uff1a<\/p>\n\n\n\n
        \/root\/ai-toolkit\/output\/computer_poster_lora_flux2_klein_1000_v1\/<\/code><\/pre>\n\n\n\n
        \u6700\u7ec8 LoRA \u5927\u6982\u7387\u5728\uff1a<\/p>\n\n\n\n
        \/root\/ai-toolkit\/output\/computer_poster_lora_flux2_klein_1000_v1\/computer_poster_lora_flux2_klein_1000_v1.safetensors<\/code><\/pre>\n\n\n\n
        6. \u590d\u5236\u65b0 LoRA \u5230 ComfyUI<\/h4>\n\n\n\n
        \u8bad\u7ec3\u5b8c\u6210\u540e\uff0c\u628a\u65b0 LoRA \u590d\u5236\u5230 ComfyUI \u7684 loras \u76ee\u5f55\uff1a<\/p>\n\n\n\n
        cp \/root\/ai-toolkit\/output\/computer_poster_lora_flux2_klein_1000_v1\/computer_poster_lora_flux2_klein_1000_v1.safetensors \\
        \/root\/ComfyUI\/models\/loras\/computer_poster_lora_flux2_klein_1000_v1.safetensors<\/code><\/pre>\n\n\n\n
        \u7136\u540e\u5237\u65b0 ComfyUI\uff0c\u5728 LoRA \u52a0\u8f7d\u5668\u91cc\u9009\u62e9\uff1a<\/p>\n\n\n\n
        computer_poster_lora_flux2_klein_1000_v1.safetensors<\/code><\/pre>\n\n\n\n
        \u521d\u59cb\u5f3a\u5ea6\u4ecd\u7136\u5efa\u8bae\uff1a<\/p>\n\n\n\n
        0.6 - 0.8<\/code><\/pre>\n\n\n\n
        7. \u4e00\u4e2a\u5b8c\u6574\u7684\u5feb\u901f\u91cd\u8bad\u547d\u4ee4\u5408\u96c6<\/h4>\n\n\n\n
        \u5982\u679c 1000 \u5f20\u56fe\u7247\u548c txt \u5df2\u7ecf\u653e\u597d\u4e86\uff0c\u53ef\u4ee5\u76f4\u63a5\u6309\u4e0b\u9762\u6d41\u7a0b\u6267\u884c\uff1a<\/p>\n\n\n\n
        cd \/root\/ComfyUI\/input\/computer_poster_lora_1000

        echo \"\u56fe\u7247\u6570\u91cf\uff1a\"
        ls *.jpg *.png *.jpeg 2>\/dev\/null | wc -l

        echo \"txt\u6570\u91cf\uff1a\"
        ls *.txt 2>\/dev\/null | wc -l

        echo \"\u5305\u542b\u89e6\u53d1\u8bcd\u7684 txt \u6570\u91cf\uff1a\"
        grep -l \"^fpoly_computer_poster_style\" *.txt | wc -l

        echo \"\u6ca1\u6709\u89e6\u53d1\u8bcd\u7684 txt\uff1a\"
        grep -L \"^fpoly_computer_poster_style\" *.txt<\/code><\/pre>\n\n\n\n
        \u786e\u8ba4\u65e0\u8bef\u540e\uff1a<\/p>\n\n\n\n
        cd \/root\/ai-toolkit

        cp config\/computer_poster_lora.yaml config\/computer_poster_lora_1000.yaml

        sed -i 's|computer_poster_lora_flux2_klein_test|computer_poster_lora_flux2_klein_1000_v1|g' config\/computer_poster_lora_1000.yaml

        sed -i 's|\/root\/ComfyUI\/input\/computer_poster_lora|\/root\/ComfyUI\/input\/computer_poster_lora_1000|g' config\/computer_poster_lora_1000.yaml

        sed -i 's|steps: 600|steps: 3000|g' config\/computer_poster_lora_1000.yaml
        sed -i 's|steps: 20|steps: 3000|g' config\/computer_poster_lora_1000.yaml

        grep -E 'name:|folder_path:|steps:|lr:|linear:|linear_alpha:|arch:|target_lin_modules:|vae_path:' config\/computer_poster_lora_1000.yaml

        python run.py config\/computer_poster_lora_1000.yaml<\/code><\/pre>\n\n\n\n
        \u8bad\u7ec3\u5b8c\u6210\u540e\uff1a<\/p>\n\n\n\n
        cp \/root\/ai-toolkit\/output\/computer_poster_lora_flux2_klein_1000_v1\/computer_poster_lora_flux2_klein_1000_v1.safetensors \\
        \/root\/ComfyUI\/models\/loras\/computer_poster_lora_flux2_klein_1000_v1.safetensors<\/code><\/pre>\n\n\n\n
        8. 1000 \u5f20\u6570\u636e\u65f6\u7684\u6ce8\u610f\u4e8b\u9879<\/h4>\n\n\n\n
        \u6570\u636e\u91cf\u589e\u52a0\u540e\uff0c\u6700\u91cd\u8981\u7684\u4e0d\u662f\u76f2\u76ee\u589e\u52a0\u8bad\u7ec3\u6b65\u6570\uff0c\u800c\u662f\u4fdd\u8bc1\u6570\u636e\u8d28\u91cf\u3002<\/p>\n\n\n\n
        \u6211\u4f1a\u7279\u522b\u6ce8\u610f\u8fd9\u51e0\u70b9\uff1a<\/p>\n\n\n\n
        1. \u56fe\u7247\u98ce\u683c\u8981\u7edf\u4e00\uff0c\u4e0d\u8981\u6df7\u5165\u592a\u591a\u65e0\u5173\u98ce\u683c
        2. \u6bcf\u5f20\u56fe\u7247\u90fd\u8981\u6709\u5bf9\u5e94 txt
        3. txt \u63cf\u8ff0\u8981\u51c6\u786e\uff0c\u4e0d\u8981\u6240\u6709\u56fe\u7247\u90fd\u5199\u5b8c\u5168\u4e00\u6837
        4. \u89e6\u53d1\u8bcd\u5fc5\u987b\u7edf\u4e00
        5. \u5148\u8dd1 3000 \u6b65\uff0c\u4e0d\u8981\u4e00\u4e0a\u6765\u8dd1\u592a\u4e45
        6. \u8bad\u7ec3\u5b8c\u6210\u540e\u6d4b\u8bd5 0.6\u30010.8\u30011.0 \u4e09\u4e2a LoRA \u5f3a\u5ea6<\/code><\/pre>\n\n\n\n
        \u5982\u679c 3000 \u6b65\u540e\u98ce\u683c\u4e0d\u591f\u660e\u663e\uff0c\u53ef\u4ee5\u7ee7\u7eed\u8bad\u7ec3\u5230\uff1a<\/p>\n\n\n\n
        5000 - 6000 steps<\/code><\/pre>\n\n\n\n
        \u5982\u679c\u51fa\u73b0\u8fc7\u62df\u5408\uff0c\u6bd4\u5982\u753b\u9762\u603b\u662f\u91cd\u590d\u540c\u4e00\u79cd\u6784\u56fe\u3001\u4ea7\u54c1\u5f62\u6001\u50f5\u786c\u3001\u80cc\u666f\u8fc7\u4e8e\u56fa\u5b9a\uff0c\u5219\u964d\u4f4e\u6b65\u6570\u6216\u4f7f\u7528\u4e2d\u95f4 checkpoint\u3002<\/p>\n\n\n\n
        9. \u63a8\u8350\u7248\u672c\u547d\u540d\u65b9\u5f0f<\/h4>\n\n\n\n
        \u4e3a\u4e86\u540e\u7eed\u7ba1\u7406\uff0c\u5efa\u8bae\u8fd9\u6837\u547d\u540d\uff1a<\/p>\n\n\n\n
        computer_poster_lora_flux2_klein_v1_15imgs_600steps.safetensors
        computer_poster_lora_flux2_klein_v2_1000imgs_3000steps.safetensors
        computer_poster_lora_flux2_klein_v3_1000imgs_5000steps.safetensors<\/code><\/pre>\n\n\n\n
        \u8fd9\u6837\u4ee5\u540e\u53ef\u4ee5\u6e05\u695a\u77e5\u9053\u6bcf\u4e2a LoRA \u662f\u7528\u591a\u5c11\u6570\u636e\u3001\u591a\u5c11\u6b65\u8bad\u7ec3\u51fa\u6765\u7684\u3002<\/p>\n\n\n\n
        \u5341\u4e09\u3001\u8fdb\u9636\u843d\u5730\uff1a\u5f53 LoRA \/ \u6a21\u578b\u8bad\u7ec3\u6210\u719f\u540e\uff0c\u5982\u4f55\u63a5\u5165\u7f51\u9875\u751f\u56fe\u4ea7\u54c1\uff1f<\/h3>\n\n\n\n
        \u5f53\u8bad\u7ec3\u6d41\u7a0b\u6253\u901a\u4ee5\u540e\uff0c\u6a21\u578b\u63a5\u5165\u7f51\u9875\u4ea7\u54c1\u7684\u6838\u5fc3\u601d\u8def\u5e76\u4e0d\u590d\u6742\uff1a\u5148\u5728 ComfyUI \u4e2d\u8c03\u901a\u5de5\u4f5c\u6d41\uff0c\u518d\u5bfc\u51fa API \u7248 JSON\uff0c\u540e\u7aef\u628a\u5b83\u4f5c\u4e3a\u63a8\u7406\u6a21\u677f\uff0c\u6839\u636e\u524d\u7aef\u4f20\u5165\u7684\u5546\u54c1\u4fe1\u606f\u52a8\u6001\u4fee\u6539\u63d0\u793a\u8bcd\u3001\u5c3a\u5bf8\u3001LoRA \u548c\u5176\u4ed6\u53c2\u6570\uff0c\u7136\u540e\u901a\u8fc7 HTTP \u8c03\u7528\u4e91\u7aef\u63a8\u7406\u670d\u52a1\u5b8c\u6210\u751f\u6210\u3002<\/p>\n\n\n\n
        \u5341\u56db\u3001LoRA \u5fae\u8c03\u90e8\u5206\u5e38\u89c1\u53c2\u6570\u7684\u529f\u80fd\u6c47\u603b\u8868<\/h3>\n\n\n\n
        \u53c2\u6570 \/ \u6587\u4ef6<\/th>\u542b\u4e49<\/th>\u4e3b\u8981\u529f\u80fd<\/th>\u8c03\u5927 \/ \u8c03\u5c0f\u7684\u5f71\u54cd<\/th><\/tr><\/thead>
        computer_poster_lora_flux2_klein_v1.safetensors<\/code><\/td>LoRA \u8bad\u7ec3\u4ea7\u7269<\/td>\u4fdd\u5b58\u201c\u7535\u8111\u7535\u5546\u6d77\u62a5\u98ce\u683c\u201d\u7684\u5fae\u8c03\u6743\u91cd\uff0c\u63a8\u7406\u65f6\u53e0\u52a0\u5230\u5e95\u6a21\u4e0a\u4f7f\u7528<\/td>\u4e0d\u662f\u53c2\u6570\uff0c\u4e0d\u80fd\u5355\u72ec\u51fa\u56fe\uff0c\u5fc5\u987b\u914d\u5408 FLUX.2 Klein \u5e95\u6a21<\/td><\/tr>
        flux-2-klein-4b.safetensors<\/code><\/td>\u8bad\u7ec3\u7528\u5e95\u6a21<\/td>LoRA \u5fae\u8c03\u65f6\u4f9d\u9644\u7684\u57fa\u7840\u751f\u56fe\u6a21\u578b<\/td>\u5e95\u6a21\u51b3\u5b9a LoRA \u9002\u914d\u5bf9\u8c61\uff0c\u6362\u5e95\u6a21\u53ef\u80fd\u4e0d\u517c\u5bb9<\/td><\/tr>
        flux-2-klein-4b-fp8.safetensors<\/code><\/td>\u63a8\u7406\u7528\u5e95\u6a21<\/td>\u5728 ComfyUI \u6587\u751f\u56fe\u5de5\u4f5c\u6d41\u91cc\u52a0\u8f7d LoRA \u540e\u5b9e\u9645\u51fa\u56fe<\/td>fp8 \u66f4\u7701\u663e\u5b58\uff0c\u9002\u5408\u90e8\u7f72\u63a8\u7406<\/td><\/tr>
        vae<\/code> \/ full_encoder_small_decoder.safetensors<\/code><\/td>VAE \u6a21\u578b<\/td>\u628a\u56fe\u7247\u538b\u7f29\u5230 latent \u6f5c\u7a7a\u95f4\uff0c\u6216\u628a latent \u89e3\u7801\u6210\u771f\u5b9e\u56fe\u7247<\/td>VAE \u4e0d\u5339\u914d\u53ef\u80fd\u5bfc\u81f4\u8bad\u7ec3\u62a5\u9519\u3001\u51fa\u56fe\u5f02\u5e38\u6216\u989c\u8272\/\u7ec6\u8282\u4e0d\u5bf9<\/td><\/tr>
        text_encoder<\/code> \/ qwen_3_4b.safetensors<\/code><\/td>\u6587\u672c\u7f16\u7801\u5668<\/td>\u628a prompt \/ caption \u8f6c\u6362\u6210\u6a21\u578b\u80fd\u7406\u89e3\u7684\u8bed\u4e49\u5411\u91cf<\/td>\u51b3\u5b9a\u6a21\u578b\u5982\u4f55\u7406\u89e3\u6587\u5b57\u63cf\u8ff0<\/td><\/tr>
        train_text_encoder: false<\/code><\/td>\u662f\u5426\u8bad\u7ec3\u6587\u672c\u7f16\u7801\u5668<\/td>\u8868\u793a\u53ea\u8bad\u7ec3\u56fe\u50cf\u751f\u6210\u6a21\u578b\u76f8\u5173 LoRA\uff0c\u4e0d\u8bad\u7ec3\u6587\u5b57\u7406\u89e3\u90e8\u5206<\/td>false<\/code> \u66f4\u7701\u663e\u5b58\u3001\u66f4\u7a33\u5b9a\uff1btrue<\/code> \u53ef\u589e\u5f3a\u7279\u5b9a\u8bcd\u7406\u89e3\uff0c\u4f46\u66f4\u8017\u8d44\u6e90<\/td><\/tr>
        trigger word<\/code> \/ fpoly_computer_poster_style<\/code><\/td>\u89e6\u53d1\u8bcd<\/td>\u8bad\u7ec3\u548c\u63a8\u7406\u65f6\u7528\u4e8e\u5524\u8d77\u7279\u5b9a LoRA \u98ce\u683c<\/td>\u63a8\u7406\u65f6\u4e0d\u5199\u89e6\u53d1\u8bcd\uff0cLoRA \u98ce\u683c\u53ef\u80fd\u4e0d\u660e\u663e<\/td><\/tr>
        caption<\/code><\/td>\u56fe\u7247\u8bf4\u660e\u6587\u672c<\/td>\u544a\u8bc9\u6a21\u578b\u6bcf\u5f20\u8bad\u7ec3\u56fe\u5305\u542b\u4ec0\u4e48\u5185\u5bb9\u548c\u98ce\u683c<\/td>caption \u8d8a\u51c6\u786e\uff0cLoRA \u8d8a\u5bb9\u6613\u5b66\u5230\u6b63\u786e\u98ce\u683c<\/td><\/tr>
        resolution<\/code><\/td>\u8bad\u7ec3\u5206\u8fa8\u7387<\/td>\u63a7\u5236\u8bad\u7ec3\u56fe\u7247\u7f29\u653e\u540e\u7684\u5c3a\u5bf8<\/td>\u5206\u8fa8\u7387\u8d8a\u9ad8\uff0c\u7ec6\u8282\u8d8a\u597d\uff0c\u4f46\u663e\u5b58\u6d88\u8017\u8d8a\u5927<\/td><\/tr>
        batch_size: 1<\/code><\/td>\u6279\u5927\u5c0f<\/td>\u6bcf\u4e00\u6b65\u8bad\u7ec3\u9001\u5165\u6a21\u578b\u7684\u56fe\u7247\u6570\u91cf<\/td>\u8d8a\u5927\u8d8a\u5403\u663e\u5b58\uff1b\u5c0f batch \u66f4\u5bb9\u6613\u5728 24GB \u663e\u5361\u4e0a\u8dd1\u901a<\/td><\/tr>
        steps<\/code><\/td>\u8bad\u7ec3\u6b65\u6570<\/td>\u63a7\u5236 LoRA \u603b\u5171\u8bad\u7ec3\u591a\u5c11\u6b21\u8fed\u4ee3<\/td>\u592a\u5c11\u5b66\u4e0d\u5230\u98ce\u683c\uff1b\u592a\u591a\u53ef\u80fd\u8fc7\u62df\u5408<\/td><\/tr>
        learning rate<\/code> \/ lr: 8e-5<\/code><\/td>\u5b66\u4e60\u7387<\/td>\u63a7\u5236\u6bcf\u4e00\u6b65\u6743\u91cd\u66f4\u65b0\u5e45\u5ea6<\/td>\u592a\u9ad8\u5bb9\u6613\u5b66\u5d29\uff1b\u592a\u4f4e\u5b66\u4e60\u6162\u3001\u98ce\u683c\u4e0d\u660e\u663e<\/td><\/tr>
        rank<\/code> \/ linear: 16<\/code><\/td>LoRA \u79e9 \/ \u5bb9\u91cf<\/td>\u51b3\u5b9a LoRA \u80fd\u5b58\u50a8\u591a\u5c11\u98ce\u683c\u4fe1\u606f<\/td>rank \u8d8a\u5927\u8868\u8fbe\u80fd\u529b\u8d8a\u5f3a\uff0c\u4f46\u66f4\u5403\u663e\u5b58\u3001\u66f4\u6613\u8fc7\u62df\u5408<\/td><\/tr>
        dtype: bf16<\/code><\/td>\u8bad\u7ec3\u6570\u503c\u7cbe\u5ea6<\/td>\u7528 bfloat16 \u964d\u4f4e\u663e\u5b58\u5360\u7528\u5e76\u4fdd\u6301\u8bad\u7ec3\u7a33\u5b9a<\/td>\u6bd4 fp32 \u7701\u663e\u5b58\uff1b\u901a\u5e38\u6bd4 fp16 \u66f4\u7a33\u5b9a<\/td><\/tr>
        quantize: true<\/code><\/td>\u91cf\u5316\u52a0\u8f7d<\/td>\u7528\u66f4\u7701\u663e\u5b58\u7684\u65b9\u5f0f\u52a0\u8f7d\u6a21\u578b<\/td>\u8282\u7701\u663e\u5b58\uff0c\u4f46\u53ef\u80fd\u7565\u5fae\u5f71\u54cd\u7cbe\u5ea6\u6216\u901f\u5ea6<\/td><\/tr>
        low_vram: true<\/code><\/td>\u4f4e\u663e\u5b58\u6a21\u5f0f<\/td>\u5c3d\u91cf\u964d\u4f4e\u8bad\u7ec3\u65f6\u663e\u5b58\u5360\u7528<\/td>\u66f4\u5bb9\u6613\u8dd1\u901a\u8bad\u7ec3\uff0c\u4f46\u8bad\u7ec3\u901f\u5ea6\u53ef\u80fd\u53d8\u6162<\/td><\/tr>
        lora strength<\/code><\/td>LoRA \u5f3a\u5ea6<\/td>\u63a8\u7406\u65f6\u63a7\u5236 LoRA \u5bf9\u6700\u7ec8\u56fe\u50cf\u7684\u5f71\u54cd\u7a0b\u5ea6<\/td>\u592a\u4f4e\u98ce\u683c\u4e0d\u660e\u663e\uff1b\u592a\u9ad8\u53ef\u80fd\u53d8\u5f62\u3001\u8fc7\u62df\u5408\u611f\u5f3a<\/td><\/tr>
        save_every<\/code> \/ checkpoint \u95f4\u9694<\/td>\u4e2d\u95f4\u6743\u91cd\u4fdd\u5b58\u9891\u7387<\/td>\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u5b9a\u671f\u4fdd\u5b58 LoRA \u68c0\u67e5\u70b9<\/td>\u65b9\u4fbf\u5bf9\u6bd4\u4e0d\u540c\u6b65\u6570\u6548\u679c\uff0c\u4e5f\u4fbf\u4e8e\u8bad\u7ec3\u4e2d\u65ad\u6062\u590d<\/td><\/tr>
        optimizer<\/code><\/td>\u4f18\u5316\u5668<\/td>\u51b3\u5b9a\u8bad\u7ec3\u65f6\u5982\u4f55\u66f4\u65b0 LoRA \u6743\u91cd<\/td>\u4e0d\u540c\u4f18\u5316\u5668\u5f71\u54cd\u6536\u655b\u901f\u5ea6\u3001\u7a33\u5b9a\u6027\u548c\u663e\u5b58\u5360\u7528<\/td><\/tr>
        dataset<\/code><\/td>\u8bad\u7ec3\u6570\u636e\u96c6<\/td>LoRA \u5b66\u4e60\u98ce\u683c\u7684\u56fe\u7247\u548c caption \u6765\u6e90<\/td>\u6570\u636e\u8d28\u91cf\u6bd4\u6570\u91cf\u66f4\u91cd\u8981\uff1b\u56fe\u7247\u98ce\u683c\u8d8a\u7edf\u4e00\uff0cLoRA \u8d8a\u5bb9\u6613\u5b66\u5230\u76ee\u6807\u98ce\u683c<\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"
        \u672c\u6587\u4e2d\u51fa\u73b0\u7684 FPI \u7edf\u4e00\u6307\u4ee3 F-PolyIma …<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-212","post","type-post","status-publish","format-standard","hentry","category-3"],"_links":{"self":[{"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/posts\/212","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/comments?post=212"}],"version-history":[{"count":17,"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/posts\/212\/revisions"}],"predecessor-version":[{"id":250,"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/posts\/212\/revisions\/250"}],"wp:attachment":[{"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/media?parent=212"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/categories?post=212"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/geocommunity.vip\/index.php\/wp-json\/wp\/v2\/tags?post=212"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}