qr2ai / diffusion_lab

Cold

Public
54 runs
L40S

Iterate in playground

Run with an API

Playground API Examples README Versions

Prediction

qr2ai/diffusion_lab:c0aee3b7ea054bc30e92d20bd3631fb379e39241b6d34b58a50356a3d9ad8e20

Model

qr2ai/diffusion_lab:c0aee3b7

jg8thr3v8drgp0cgqmg8z86d88

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

18m 30s

Created

11 months ago

Input

seed: -1
prompt: Wooden Style
sampler: DPM++ Karras SDE
strength: 0.9
batch_size: 1
guidance_scale: 7.5
negative_prompt: ugly, disfigured, low quality, blurry, nsfw
qr_code_content: Hello
num_inference_steps: 40
controlnet_conditioning_scale: 1.5

{
  "seed": -1,
  "prompt": "Wooden Style",
  "sampler": "DPM++ Karras SDE",
  "strength": 0.9,
  "batch_size": 1,
  "guidance_scale": 7.5,
  "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
  "qr_code_content": "Hello",
  "num_inference_steps": 40,
  "controlnet_conditioning_scale": 1.5
}

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 qr2ai/diffusion_lab using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "qr2ai/diffusion_lab:c0aee3b7ea054bc30e92d20bd3631fb379e39241b6d34b58a50356a3d9ad8e20",
  {
    input: {
      seed: -1,
      prompt: "Wooden Style",
      sampler: "DPM++ Karras SDE",
      strength: 0.9,
      batch_size: 1,
      guidance_scale: 7.5,
      negative_prompt: "ugly, disfigured, low quality, blurry, nsfw",
      qr_code_content: "Hello",
      num_inference_steps: 40,
      controlnet_conditioning_scale: 1.5
    }
  }
);

// 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 qr2ai/diffusion_lab using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "qr2ai/diffusion_lab:c0aee3b7ea054bc30e92d20bd3631fb379e39241b6d34b58a50356a3d9ad8e20",
    input={
        "seed": -1,
        "prompt": "Wooden Style",
        "sampler": "DPM++ Karras SDE",
        "strength": 0.9,
        "batch_size": 1,
        "guidance_scale": 7.5,
        "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
        "qr_code_content": "Hello",
        "num_inference_steps": 40,
        "controlnet_conditioning_scale": 1.5
    }
)
print(output)

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

Run qr2ai/diffusion_lab 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": "qr2ai/diffusion_lab:c0aee3b7ea054bc30e92d20bd3631fb379e39241b6d34b58a50356a3d9ad8e20",
    "input": {
      "seed": -1,
      "prompt": "Wooden Style",
      "sampler": "DPM++ Karras SDE",
      "strength": 0.9,
      "batch_size": 1,
      "guidance_scale": 7.5,
      "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
      "qr_code_content": "Hello",
      "num_inference_steps": 40,
      "controlnet_conditioning_scale": 1.5
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-07-16T20:17:31.373499Z",
  "created_at": "2024-07-16T19:59:00.931000Z",
  "data_removed": false,
  "error": null,
  "id": "jg8thr3v8drgp0cgqmg8z86d88",
  "input": {
    "seed": -1,
    "prompt": "Wooden Style",
    "sampler": "DPM++ Karras SDE",
    "strength": 0.9,
    "batch_size": 1,
    "guidance_scale": 7.5,
    "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
    "qr_code_content": "Hello",
    "num_inference_steps": 40,
    "controlnet_conditioning_scale": 1.5
  },
  "logs": "Generating QR Code from content\n  0%|          | 0/36 [00:00<?, ?it/s]\n  3%|▎         | 1/36 [00:00<00:06,  5.36it/s]\n  6%|▌         | 2/36 [00:00<00:05,  6.46it/s]\n  8%|▊         | 3/36 [00:00<00:04,  6.92it/s]\n 11%|█         | 4/36 [00:00<00:04,  7.16it/s]\n 14%|█▍        | 5/36 [00:00<00:04,  7.29it/s]\n 17%|█▋        | 6/36 [00:00<00:04,  7.37it/s]\n 19%|█▉        | 7/36 [00:00<00:03,  7.42it/s]\n 22%|██▏       | 8/36 [00:01<00:03,  7.46it/s]\n 25%|██▌       | 9/36 [00:01<00:03,  7.48it/s]\n 28%|██▊       | 10/36 [00:01<00:03,  7.49it/s]\n 31%|███       | 11/36 [00:01<00:03,  7.52it/s]\n 33%|███▎      | 12/36 [00:01<00:03,  7.52it/s]\n 36%|███▌      | 13/36 [00:01<00:03,  7.52it/s]\n 39%|███▉      | 14/36 [00:01<00:02,  7.52it/s]\n 42%|████▏     | 15/36 [00:02<00:02,  7.52it/s]\n 44%|████▍     | 16/36 [00:02<00:02,  7.52it/s]\n 47%|████▋     | 17/36 [00:02<00:02,  7.52it/s]\n 50%|█████     | 18/36 [00:02<00:02,  7.52it/s]\n 53%|█████▎    | 19/36 [00:02<00:02,  7.52it/s]\n 56%|█████▌    | 20/36 [00:02<00:02,  7.52it/s]\n 58%|█████▊    | 21/36 [00:02<00:01,  7.52it/s]\n 61%|██████    | 22/36 [00:02<00:01,  7.51it/s]\n 64%|██████▍   | 23/36 [00:03<00:01,  7.52it/s]\n 67%|██████▋   | 24/36 [00:03<00:01,  7.51it/s]\n 69%|██████▉   | 25/36 [00:03<00:01,  7.52it/s]\n 72%|███████▏  | 26/36 [00:03<00:01,  7.52it/s]\n 75%|███████▌  | 27/36 [00:03<00:01,  7.51it/s]\n 78%|███████▊  | 28/36 [00:03<00:01,  7.51it/s]\n 81%|████████  | 29/36 [00:03<00:00,  7.52it/s]\n 83%|████████▎ | 30/36 [00:04<00:00,  7.51it/s]\n 86%|████████▌ | 31/36 [00:04<00:00,  7.52it/s]\n 89%|████████▉ | 32/36 [00:04<00:00,  7.51it/s]\n 92%|█████████▏| 33/36 [00:04<00:00,  7.50it/s]\n 94%|█████████▍| 34/36 [00:04<00:00,  7.51it/s]\n 97%|█████████▋| 35/36 [00:04<00:00,  7.51it/s]\n100%|██████████| 36/36 [00:04<00:00,  7.50it/s]\n100%|██████████| 36/36 [00:04<00:00,  7.44it/s]",
  "metrics": {
    "predict_time": 6.417135183,
    "total_time": 1110.442499
  },
  "output": [
    "https://replicate.delivery/pbxt/c2M1iqgWl5bjIBm8ioAnyj0GMfYefDgirwOHiO942fzt1hkMB/output-0.png"
  ],
  "started_at": "2024-07-16T20:17:24.956364Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/jg8thr3v8drgp0cgqmg8z86d88",
    "cancel": "https://api.replicate.com/v1/predictions/jg8thr3v8drgp0cgqmg8z86d88/cancel"
  },
  "version": "c0aee3b7ea054bc30e92d20bd3631fb379e39241b6d34b58a50356a3d9ad8e20"
}

Generated in

6.4 seconds

Tweak it ShareReport

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