fofr / sdxl-labyrinths

{
  "width": 1024,
  "height": 1024,
  "prompt": "A photo of a poltergeist destroying a kitchen in the style of TOK",
  "refine": "expert_ensemble_refiner",
  "scheduler": "K_EULER",
  "lora_scale": 0.6,
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.95,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/sdxl-labyrinths using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/sdxl-labyrinths:fdc5500d0347656e81610a9800519c031f8331adea4fa2a0b4291faf72ae1e9f",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "A photo of a poltergeist destroying a kitchen in the style of TOK",
      refine: "expert_ensemble_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 1,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.95,
      negative_prompt: "",
      prompt_strength: 0.8,
      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]);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run fofr/sdxl-labyrinths using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/sdxl-labyrinths:fdc5500d0347656e81610a9800519c031f8331adea4fa2a0b4291faf72ae1e9f",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "A photo of a poltergeist destroying a kitchen in the style of TOK",
        "refine": "expert_ensemble_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.6,
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.95,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run fofr/sdxl-labyrinths using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "fofr/sdxl-labyrinths:fdc5500d0347656e81610a9800519c031f8331adea4fa2a0b4291faf72ae1e9f",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "A photo of a poltergeist destroying a kitchen in the style of TOK",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.95,
      "negative_prompt": "",
      "prompt_strength": 0.8,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2023-09-01T22:38:08.223364Z",
  "created_at": "2023-09-01T22:37:53.503336Z",
  "data_removed": false,
  "error": null,
  "id": "bd3l4flbluqbsaxouju6uqy5fq",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "A photo of a poltergeist destroying a kitchen in the style of TOK",
    "refine": "expert_ensemble_refiner",
    "scheduler": "K_EULER",
    "lora_scale": 0.6,
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "apply_watermark": false,
    "high_noise_frac": 0.95,
    "negative_prompt": "",
    "prompt_strength": 0.8,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 59099\nPrompt: A photo of a poltergeist destroying a kitchen in the style of <s0><s1>\ntxt2img mode\n  0%|          | 0/47 [00:00<?, ?it/s]\n  2%|▏         | 1/47 [00:00<00:12,  3.59it/s]\n  4%|▍         | 2/47 [00:00<00:12,  3.66it/s]\n  6%|▋         | 3/47 [00:00<00:11,  3.68it/s]\n  9%|▊         | 4/47 [00:01<00:11,  3.67it/s]\n 11%|█         | 5/47 [00:01<00:11,  3.68it/s]\n 13%|█▎        | 6/47 [00:01<00:11,  3.68it/s]\n 15%|█▍        | 7/47 [00:01<00:10,  3.68it/s]\n 17%|█▋        | 8/47 [00:02<00:10,  3.68it/s]\n 19%|█▉        | 9/47 [00:02<00:10,  3.68it/s]\n 21%|██▏       | 10/47 [00:02<00:10,  3.68it/s]\n 23%|██▎       | 11/47 [00:02<00:09,  3.68it/s]\n 26%|██▌       | 12/47 [00:03<00:09,  3.68it/s]\n 28%|██▊       | 13/47 [00:03<00:09,  3.68it/s]\n 30%|██▉       | 14/47 [00:03<00:08,  3.68it/s]\n 32%|███▏      | 15/47 [00:04<00:08,  3.68it/s]\n 34%|███▍      | 16/47 [00:04<00:08,  3.68it/s]\n 36%|███▌      | 17/47 [00:04<00:08,  3.68it/s]\n 38%|███▊      | 18/47 [00:04<00:07,  3.67it/s]\n 40%|████      | 19/47 [00:05<00:07,  3.67it/s]\n 43%|████▎     | 20/47 [00:05<00:07,  3.67it/s]\n 45%|████▍     | 21/47 [00:05<00:07,  3.67it/s]\n 47%|████▋     | 22/47 [00:05<00:06,  3.67it/s]\n 49%|████▉     | 23/47 [00:06<00:06,  3.67it/s]\n 51%|█████     | 24/47 [00:06<00:06,  3.67it/s]\n 53%|█████▎    | 25/47 [00:06<00:05,  3.67it/s]\n 55%|█████▌    | 26/47 [00:07<00:05,  3.68it/s]\n 57%|█████▋    | 27/47 [00:07<00:05,  3.68it/s]\n 60%|█████▉    | 28/47 [00:07<00:05,  3.69it/s]\n 62%|██████▏   | 29/47 [00:07<00:04,  3.69it/s]\n 64%|██████▍   | 30/47 [00:08<00:04,  3.69it/s]\n 66%|██████▌   | 31/47 [00:08<00:04,  3.69it/s]\n 68%|██████▊   | 32/47 [00:08<00:04,  3.69it/s]\n 70%|███████   | 33/47 [00:08<00:03,  3.69it/s]\n 72%|███████▏  | 34/47 [00:09<00:03,  3.69it/s]\n 74%|███████▍  | 35/47 [00:09<00:03,  3.69it/s]\n 77%|███████▋  | 36/47 [00:09<00:02,  3.69it/s]\n 79%|███████▊  | 37/47 [00:10<00:02,  3.69it/s]\n 81%|████████  | 38/47 [00:10<00:02,  3.69it/s]\n 83%|████████▎ | 39/47 [00:10<00:02,  3.69it/s]\n 85%|████████▌ | 40/47 [00:10<00:01,  3.69it/s]\n 87%|████████▋ | 41/47 [00:11<00:01,  3.69it/s]\n 89%|████████▉ | 42/47 [00:11<00:01,  3.69it/s]\n 91%|█████████▏| 43/47 [00:11<00:01,  3.69it/s]\n 94%|█████████▎| 44/47 [00:11<00:00,  3.69it/s]\n 96%|█████████▌| 45/47 [00:12<00:00,  3.69it/s]\n 98%|█████████▊| 46/47 [00:12<00:00,  3.69it/s]\n100%|██████████| 47/47 [00:12<00:00,  3.69it/s]\n100%|██████████| 47/47 [00:12<00:00,  3.68it/s]\n  0%|          | 0/3 [00:00<?, ?it/s]\n 33%|███▎      | 1/3 [00:00<00:00,  4.23it/s]\n 67%|██████▋   | 2/3 [00:00<00:00,  4.29it/s]\n100%|██████████| 3/3 [00:00<00:00,  4.31it/s]\n100%|██████████| 3/3 [00:00<00:00,  4.30it/s]",
  "metrics": {
    "predict_time": 14.795907,
    "total_time": 14.720028
  },
  "output": [
    "https://pbxt.replicate.delivery/i7beWQe6pnkOfIUlQgLOw3eIx5uUteGfUzfzkNsrGzA5nzAwIA/out-0.png"
  ],
  "started_at": "2023-09-01T22:37:53.427457Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/bd3l4flbluqbsaxouju6uqy5fq",
    "cancel": "https://api.replicate.com/v1/predictions/bd3l4flbluqbsaxouju6uqy5fq/cancel"
  },
  "version": "fdc5500d0347656e81610a9800519c031f8331adea4fa2a0b4291faf72ae1e9f"
}

Generated in

14.8 seconds

Tweak it ShareReport

Using seed: 59099
Prompt: A photo of a poltergeist destroying a kitchen in the style of <s0><s1>
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