const output = await replicate.run(
  "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
  {
    input: {
      seed: 12345,
      width: 1024,
      height: 1024,
      prompt: "a legendary bird is flying (under the sea)1.4 water staring at a multicolor sky, wallpaper, corals and fish are swimming around",
      refine: "expert_ensemble_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: true,
      high_noise_frac: 0.8,
      negative_prompt: "ugly, blurry, realistic",
      prompt_strength: 0.8,
      prompt_weighting: true,
      num_inference_steps: 50
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

output = replicate.run(
    "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
    input={
        "seed": 12345,
        "width": 1024,
        "height": 1024,
        "prompt": "a legendary bird is flying (under the sea)1.4 water staring at a multicolor sky, wallpaper, corals and fish are swimming around",
        "refine": "expert_ensemble_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.6,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": True,
        "high_noise_frac": 0.8,
        "negative_prompt": "ugly, blurry, realistic",
        "prompt_strength": 0.8,
        "prompt_weighting": True,
        "num_inference_steps": 50
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
    "input": {
      "seed": 12345,
      "width": 1024,
      "height": 1024,
      "prompt": "a legendary bird is flying (under the sea)1.4 water staring at a multicolor sky, wallpaper, corals and fish are swimming around",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": true,
      "high_noise_frac": 0.8,
      "negative_prompt": "ugly, blurry, realistic",
      "prompt_strength": 0.8,
      "prompt_weighting": true,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/fermatresearch/sdxl-weighting-prompts@sha256:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7 \
  -i 'seed=12345' \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a legendary bird is flying (under the sea)1.4 water staring at a multicolor sky, wallpaper, corals and fish are swimming around"' \
  -i 'refine="expert_ensemble_refiner"' \
  -i 'scheduler="K_EULER"' \
  -i 'lora_scale=0.6' \
  -i 'num_outputs=1' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=true' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="ugly, blurry, realistic"' \
  -i 'prompt_strength=0.8' \
  -i 'prompt_weighting=true' \
  -i 'num_inference_steps=50'

docker run -d -p 5000:5000 --gpus=all r8.im/fermatresearch/sdxl-weighting-prompts@sha256:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": 12345,
      "width": 1024,
      "height": 1024,
      "prompt": "a legendary bird is flying (under the sea)1.4 water staring at a multicolor sky, wallpaper, corals and fish are swimming around",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": true,
      "high_noise_frac": 0.8,
      "negative_prompt": "ugly, blurry, realistic",
      "prompt_strength": 0.8,
      "prompt_weighting": true,
      "num_inference_steps": 50
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
  {
    input: {
      seed: 12345,
      width: 1024,
      height: 1024,
      prompt: "a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, corals and fish are swimming around",
      refine: "expert_ensemble_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: true,
      high_noise_frac: 0.8,
      negative_prompt: "ugly, blurry, realistic",
      prompt_strength: 0.8,
      prompt_weighting: true,
      num_inference_steps: 50
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

output = replicate.run(
    "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
    input={
        "seed": 12345,
        "width": 1024,
        "height": 1024,
        "prompt": "a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, corals and fish are swimming around",
        "refine": "expert_ensemble_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.6,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": True,
        "high_noise_frac": 0.8,
        "negative_prompt": "ugly, blurry, realistic",
        "prompt_strength": 0.8,
        "prompt_weighting": True,
        "num_inference_steps": 50
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
    "input": {
      "seed": 12345,
      "width": 1024,
      "height": 1024,
      "prompt": "a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, corals and fish are swimming around",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": true,
      "high_noise_frac": 0.8,
      "negative_prompt": "ugly, blurry, realistic",
      "prompt_strength": 0.8,
      "prompt_weighting": true,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/fermatresearch/sdxl-weighting-prompts@sha256:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7 \
  -i 'seed=12345' \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, corals and fish are swimming around"' \
  -i 'refine="expert_ensemble_refiner"' \
  -i 'scheduler="K_EULER"' \
  -i 'lora_scale=0.6' \
  -i 'num_outputs=1' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=true' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="ugly, blurry, realistic"' \
  -i 'prompt_strength=0.8' \
  -i 'prompt_weighting=true' \
  -i 'num_inference_steps=50'

docker run -d -p 5000:5000 --gpus=all r8.im/fermatresearch/sdxl-weighting-prompts@sha256:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": 12345,
      "width": 1024,
      "height": 1024,
      "prompt": "a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, corals and fish are swimming around",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": true,
      "high_noise_frac": 0.8,
      "negative_prompt": "ugly, blurry, realistic",
      "prompt_strength": 0.8,
      "prompt_weighting": true,
      "num_inference_steps": 50
    }
  }' \
  http://localhost:5000/predictions

const output = await replicate.run(
  "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
  {
    input: {
      seed: 12345,
      width: 1024,
      height: 1024,
      prompt: "a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, (corals and fish are swimming around)0.4",
      refine: "expert_ensemble_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: true,
      high_noise_frac: 0.8,
      negative_prompt: "ugly, blurry, realistic",
      prompt_strength: 0.8,
      prompt_weighting: true,
      num_inference_steps: 50
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

output = replicate.run(
    "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
    input={
        "seed": 12345,
        "width": 1024,
        "height": 1024,
        "prompt": "a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, (corals and fish are swimming around)0.4",
        "refine": "expert_ensemble_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.6,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": True,
        "high_noise_frac": 0.8,
        "negative_prompt": "ugly, blurry, realistic",
        "prompt_strength": 0.8,
        "prompt_weighting": True,
        "num_inference_steps": 50
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "fermatresearch/sdxl-weighting-prompts:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7",
    "input": {
      "seed": 12345,
      "width": 1024,
      "height": 1024,
      "prompt": "a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, (corals and fish are swimming around)0.4",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": true,
      "high_noise_frac": 0.8,
      "negative_prompt": "ugly, blurry, realistic",
      "prompt_strength": 0.8,
      "prompt_weighting": true,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

cog predict r8.im/fermatresearch/sdxl-weighting-prompts@sha256:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7 \
  -i 'seed=12345' \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, (corals and fish are swimming around)0.4"' \
  -i 'refine="expert_ensemble_refiner"' \
  -i 'scheduler="K_EULER"' \
  -i 'lora_scale=0.6' \
  -i 'num_outputs=1' \
  -i 'guidance_scale=7.5' \
  -i 'apply_watermark=true' \
  -i 'high_noise_frac=0.8' \
  -i 'negative_prompt="ugly, blurry, realistic"' \
  -i 'prompt_strength=0.8' \
  -i 'prompt_weighting=true' \
  -i 'num_inference_steps=50'

docker run -d -p 5000:5000 --gpus=all r8.im/fermatresearch/sdxl-weighting-prompts@sha256:66175a2993706e1721076d5c7f92f0c81ec6d065ec20717527f05dd8528a1fc7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": 12345,
      "width": 1024,
      "height": 1024,
      "prompt": "a legendary bird is flying under the sea water staring at a multicolor sky, wallpaper, (corals and fish are swimming around)0.4",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": true,
      "high_noise_frac": 0.8,
      "negative_prompt": "ugly, blurry, realistic",
      "prompt_strength": 0.8,
      "prompt_weighting": true,
      "num_inference_steps": 50
    }
  }' \
  http://localhost:5000/predictions