const output = await replicate.run(
  "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
  {
    input: {
      image: "https://replicate.delivery/pbxt/JXq6GWMe7YRjxu8Mc7gGkLecuqrnBI23rrX8bj7F0m8iYyjk/%E9%A4%90%E6%A1%8C%E8%83%8C%E6%99%AF1.png",
      width: 768,
      height: 512,
      prompt: "a photo of TOK plate, a glass of Bundaberg juice and vegetable salad on a table",
      refine: "no_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.8,
      num_outputs: 2,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);
console.log(output);

output = replicate.run(
    "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    input={
        "image": "https://replicate.delivery/pbxt/JXq6GWMe7YRjxu8Mc7gGkLecuqrnBI23rrX8bj7F0m8iYyjk/%E9%A4%90%E6%A1%8C%E8%83%8C%E6%99%AF1.png",
        "width": 768,
        "height": 512,
        "prompt": "a photo of TOK plate, a glass of Bundaberg juice and vegetable salad on a table",
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.8,
        "num_outputs": 2,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    "input": {
      "image": "https://replicate.delivery/pbxt/JXq6GWMe7YRjxu8Mc7gGkLecuqrnBI23rrX8bj7F0m8iYyjk/%E9%A4%90%E6%A1%8C%E8%83%8C%E6%99%AF1.png",
      "width": 768,
      "height": 512,
      "prompt": "a photo of TOK plate, a glass of Bundaberg juice and vegetable salad on a table",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29 \
  -i 'image="https://replicate.delivery/pbxt/JXq6GWMe7YRjxu8Mc7gGkLecuqrnBI23rrX8bj7F0m8iYyjk/%E9%A4%90%E6%A1%8C%E8%83%8C%E6%99%AF1.png"' \
  -i 'width=768' \
  -i 'height=512' \
  -i 'prompt="a photo of TOK plate, a glass of Bundaberg juice and vegetable salad on a table"' \
  -i 'refine="no_refiner"' \
  -i 'scheduler="K_EULER"' \
  -i 'lora_scale=0.8' \
  -i 'num_outputs=2' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=false' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw"' \
  -i 'prompt_strength=0.8' \
  -i 'num_inference_steps=30'

docker run -d -p 5000:5000 --gpus=all r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "image": "https://replicate.delivery/pbxt/JXq6GWMe7YRjxu8Mc7gGkLecuqrnBI23rrX8bj7F0m8iYyjk/%E9%A4%90%E6%A1%8C%E8%83%8C%E6%99%AF1.png",
      "width": 768,
      "height": 512,
      "prompt": "a photo of TOK plate, a glass of Bundaberg juice and vegetable salad on a table",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK plate on a cloth on the table",
      refine: "no_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.8,
      num_outputs: 2,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);
console.log(output);

output = replicate.run(
    "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK plate on a cloth on the table",
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.8,
        "num_outputs": 2,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK plate on a cloth on the table",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29 \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a photo of TOK plate on a cloth on the table"' \
  -i 'refine="no_refiner"' \
  -i 'scheduler="K_EULER"' \
  -i 'lora_scale=0.8' \
  -i 'num_outputs=2' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=false' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw"' \
  -i 'prompt_strength=0.8' \
  -i 'num_inference_steps=30'

docker run -d -p 5000:5000 --gpus=all r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK plate on a cloth on the table",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK plates, these are some vegetables on a plate with tomatoes in the background",
      refine: "no_refiner",
      scheduler: "DPMSolverMultistep",
      lora_scale: 0.8,
      num_outputs: 2,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);
console.log(output);

output = replicate.run(
    "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK plates, these are some vegetables on a plate with tomatoes in the background",
        "refine": "no_refiner",
        "scheduler": "DPMSolverMultistep",
        "lora_scale": 0.8,
        "num_outputs": 2,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK plates, these are some vegetables on a plate with tomatoes in the background",
      "refine": "no_refiner",
      "scheduler": "DPMSolverMultistep",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29 \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a photo of TOK plates, these are some vegetables on a plate with tomatoes in the background"' \
  -i 'refine="no_refiner"' \
  -i 'scheduler="DPMSolverMultistep"' \
  -i 'lora_scale=0.8' \
  -i 'num_outputs=2' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=false' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw"' \
  -i 'prompt_strength=0.8' \
  -i 'num_inference_steps=30'

docker run -d -p 5000:5000 --gpus=all r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK plates, these are some vegetables on a plate with tomatoes in the background",
      "refine": "no_refiner",
      "scheduler": "DPMSolverMultistep",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK plate with Thai style rice and vegetables and fruit on a plate",
      refine: "no_refiner",
      scheduler: "DPMSolverMultistep",
      lora_scale: 0.8,
      num_outputs: 2,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);
console.log(output);

output = replicate.run(
    "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK plate with Thai style rice and vegetables and fruit on a plate",
        "refine": "no_refiner",
        "scheduler": "DPMSolverMultistep",
        "lora_scale": 0.8,
        "num_outputs": 2,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK plate with Thai style rice and vegetables and fruit on a plate",
      "refine": "no_refiner",
      "scheduler": "DPMSolverMultistep",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29 \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a photo of TOK plate with Thai style rice and vegetables and fruit on a plate"' \
  -i 'refine="no_refiner"' \
  -i 'scheduler="DPMSolverMultistep"' \
  -i 'lora_scale=0.8' \
  -i 'num_outputs=2' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=false' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw"' \
  -i 'prompt_strength=0.8' \
  -i 'num_inference_steps=30'

docker run -d -p 5000:5000 --gpus=all r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK plate with Thai style rice and vegetables and fruit on a plate",
      "refine": "no_refiner",
      "scheduler": "DPMSolverMultistep",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK several plates on a table, several people hold up a bottle of ginger beer behind table remote background shot",
      refine: "no_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.8,
      num_outputs: 2,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);
console.log(output);

output = replicate.run(
    "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK several plates on a table, several people hold up a bottle of ginger beer behind table remote background shot",
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.8,
        "num_outputs": 2,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK several plates on a table, several people hold up a bottle of ginger beer behind table remote background shot",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29 \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a photo of TOK several plates on a table, several people hold up a bottle of ginger beer behind table remote background shot"' \
  -i 'refine="no_refiner"' \
  -i 'scheduler="K_EULER"' \
  -i 'lora_scale=0.8' \
  -i 'num_outputs=2' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=false' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw"' \
  -i 'prompt_strength=0.8' \
  -i 'num_inference_steps=30'

docker run -d -p 5000:5000 --gpus=all r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK several plates on a table, several people hold up a bottle of ginger beer behind table remote background shot",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a photo of TOK plate, someone is eating with a sauce",
      refine: "no_refiner",
      scheduler: "DPMSolverMultistep",
      lora_scale: 0.8,
      num_outputs: 2,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);
console.log(output);

output = replicate.run(
    "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a photo of TOK plate, someone is eating with a sauce",
        "refine": "no_refiner",
        "scheduler": "DPMSolverMultistep",
        "lora_scale": 0.8,
        "num_outputs": 2,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK plate, someone is eating with a sauce",
      "refine": "no_refiner",
      "scheduler": "DPMSolverMultistep",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29 \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a photo of TOK plate, someone is eating with a sauce"' \
  -i 'refine="no_refiner"' \
  -i 'scheduler="DPMSolverMultistep"' \
  -i 'lora_scale=0.8' \
  -i 'num_outputs=2' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=false' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw"' \
  -i 'prompt_strength=0.8' \
  -i 'num_inference_steps=30'

docker run -d -p 5000:5000 --gpus=all r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a photo of TOK plate, someone is eating with a sauce",
      "refine": "no_refiner",
      "scheduler": "DPMSolverMultistep",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
  {
    input: {
      width: 1024,
      height: 512,
      prompt: "a photo of TOK plates, 3 plates are lined up with drinks on a table in a garden restaurant",
      refine: "no_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.8,
      num_outputs: 2,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);
console.log(output);

output = replicate.run(
    "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    input={
        "width": 1024,
        "height": 512,
        "prompt": "a photo of TOK plates, 3 plates are lined up with drinks on a table in a garden restaurant",
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.8,
        "num_outputs": 2,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    "input": {
      "width": 1024,
      "height": 512,
      "prompt": "a photo of TOK plates, 3 plates are lined up with drinks on a table in a garden restaurant",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29 \
  -i 'width=1024' \
  -i 'height=512' \
  -i 'prompt="a photo of TOK plates, 3 plates are lined up with drinks on a table in a garden restaurant"' \
  -i 'refine="no_refiner"' \
  -i 'scheduler="K_EULER"' \
  -i 'lora_scale=0.8' \
  -i 'num_outputs=2' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=false' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw"' \
  -i 'prompt_strength=0.8' \
  -i 'num_inference_steps=30'

docker run -d -p 5000:5000 --gpus=all r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 1024,
      "height": 512,
      "prompt": "a photo of TOK plates, 3 plates are lined up with drinks on a table in a garden restaurant",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
  {
    input: {
      width: 1024,
      height: 512,
      prompt: "a photo of TOK plate, a bowl of spicy meat and and a curry crab with Bundaberg juice drinks on a table in a garden restaurant",
      refine: "no_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.8,
      num_outputs: 2,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      prompt_strength: 0.8,
      num_inference_steps: 30
    }
  }
);
console.log(output);

output = replicate.run(
    "peter65374/sdxl-gongbao:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    input={
        "width": 1024,
        "height": 512,
        "prompt": "a photo of TOK plate, a bowl of spicy meat and and a curry crab with Bundaberg juice drinks on a table in a garden restaurant",
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.8,
        "num_outputs": 2,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
        "prompt_strength": 0.8,
        "num_inference_steps": 30
    }
)
print(output)

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29",
    "input": {
      "width": 1024,
      "height": 512,
      "prompt": "a photo of TOK plate, a bowl of spicy meat and and a curry crab with Bundaberg juice drinks on a table in a garden restaurant",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29 \
  -i 'width=1024' \
  -i 'height=512' \
  -i 'prompt="a photo of TOK plate, a bowl of spicy meat and and a curry crab with Bundaberg juice drinks on a table in a garden restaurant"' \
  -i 'refine="no_refiner"' \
  -i 'scheduler="K_EULER"' \
  -i 'lora_scale=0.8' \
  -i 'num_outputs=2' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=false' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw"' \
  -i 'prompt_strength=0.8' \
  -i 'num_inference_steps=30'

docker run -d -p 5000:5000 --gpus=all r8.im/peter65374/sdxl-gongbao@sha256:d1482b21e7b16dd914a74db9e9d877341f2c3197a25c695afac57402708fac29
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 1024,
      "height": 512,
      "prompt": "a photo of TOK plate, a bowl of spicy meat and and a curry crab with Bundaberg juice drinks on a table in a garden restaurant",
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.8,
      "num_outputs": 2,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "unrealistic, poor texture, poor quality, bad material, soft detail, bad pictures, (bad hand), ((low quality)), ((worst quality)), nsfw",
      "prompt_strength": 0.8,
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions