suryakantk94/whiteclaw-db – Run with an API on Replicate

Input

prompt

string

Shift + Return to add a new line

a photo of a person sitting with a TOK can in his hands in a football stadium. there is a display of different flavors of can in the bottom right side of the picture.a photo of a person sitting with a TOK can in his hands in a football stadium. there is a display of different flavors of can in the bottom right side of the picture.

Input prompt

Default: "a photo of cjw"

negative_prompt

string

Shift + Return to add a new line

Specify things to not see in the output

image

file

A starting image from which to generate variations (aka 'img2img'). If this input is set, the `width` and `height` inputs are ignored and the output will have the same dimensions as the input image.

width

integer

Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 512

height

integer

Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 512

prompt_strength

number

Prompt strength when using init image. 1.0 corresponds to full destruction of information in init image

Default: 0.8

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7.5

scheduler

string

Choose a scheduler

Default: "DDIM"

seed

integer

Random seed. Leave blank to randomize the seed

disable_safety_check

boolean

Disable safety check. Use at your own risk!

Default: false

Run this model in Node.js with one line of code:

npx create-replicate --model=suryakantk94/whiteclaw-db

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

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

Run suryakantk94/whiteclaw-db using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "suryakantk94/whiteclaw-db:d6659251793b795fca3f80006f36005859c73fdc9d1b112a432a120b1b0ad311",
  {
    input: {
      width: 512,
      height: 512,
      prompt: "a photo of a person sitting with a TOK can in his hands in a football stadium. there is a display of different flavors of can in the bottom right side of the picture.",
      scheduler: "DDIM",
      num_outputs: 1,
      guidance_scale: 7.5,
      prompt_strength: 0.8,
      num_inference_steps: 50,
      disable_safety_check: false
    }
  }
);

// 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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run suryakantk94/whiteclaw-db using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "suryakantk94/whiteclaw-db:d6659251793b795fca3f80006f36005859c73fdc9d1b112a432a120b1b0ad311",
    input={
        "width": 512,
        "height": 512,
        "prompt": "a photo of a person sitting with a TOK can in his hands in a football stadium. there is a display of different flavors of can in the bottom right side of the picture.",
        "scheduler": "DDIM",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "prompt_strength": 0.8,
        "num_inference_steps": 50,
        "disable_safety_check": False
    }
)
print(output)

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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run suryakantk94/whiteclaw-db 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": "suryakantk94/whiteclaw-db:d6659251793b795fca3f80006f36005859c73fdc9d1b112a432a120b1b0ad311",
    "input": {
      "width": 512,
      "height": 512,
      "prompt": "a photo of a person sitting with a TOK can in his hands in a football stadium. there is a display of different flavors of can in the bottom right side of the picture.",
      "scheduler": "DDIM",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "prompt_strength": 0.8,
      "num_inference_steps": 50,
      "disable_safety_check": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-06-28T21:52:08.901738Z",
  "created_at": "2024-06-28T21:50:15.744000Z",
  "data_removed": false,
  "error": null,
  "id": "p3343w6wr1rgm0cgc39sh11m7c",
  "input": {
    "width": 512,
    "height": 512,
    "prompt": "a photo of a person sitting with a TOK can in his hands in a football stadium. there is a display of different flavors of can in the bottom right side of the picture.",
    "scheduler": "DDIM",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "prompt_strength": 0.8,
    "num_inference_steps": 50,
    "disable_safety_check": false
  },
  "logs": "Using seed: 6789\nusing txt2img\n  0%|          | 0/50 [00:00<?, ?it/s]\n  2%|▏         | 1/50 [00:12<10:14, 12.55s/it]\n  6%|▌         | 3/50 [00:12<02:34,  3.30s/it]\n 10%|█         | 5/50 [00:12<01:13,  1.63s/it]\n 14%|█▍        | 7/50 [00:12<00:41,  1.04it/s]\n 18%|█▊        | 9/50 [00:13<00:25,  1.61it/s]\n 22%|██▏       | 11/50 [00:13<00:16,  2.36it/s]\n 26%|██▌       | 13/50 [00:13<00:11,  3.31it/s]\n 30%|███       | 15/50 [00:13<00:07,  4.48it/s]\n 34%|███▍      | 17/50 [00:13<00:05,  5.86it/s]\n 38%|███▊      | 19/50 [00:13<00:04,  7.38it/s]\n 42%|████▏     | 21/50 [00:13<00:03,  8.98it/s]\n 46%|████▌     | 23/50 [00:13<00:02, 10.54it/s]\n 50%|█████     | 25/50 [00:13<00:02, 11.99it/s]\n 54%|█████▍    | 27/50 [00:14<00:01, 13.24it/s]\n 58%|█████▊    | 29/50 [00:14<00:01, 14.30it/s]\n 62%|██████▏   | 31/50 [00:14<00:01, 15.15it/s]\n 66%|██████▌   | 33/50 [00:14<00:01, 15.80it/s]\n 70%|███████   | 35/50 [00:14<00:00, 16.28it/s]\n 74%|███████▍  | 37/50 [00:14<00:00, 16.64it/s]\n 78%|███████▊  | 39/50 [00:14<00:00, 16.90it/s]\n 82%|████████▏ | 41/50 [00:14<00:00, 17.09it/s]\n 86%|████████▌ | 43/50 [00:14<00:00, 17.22it/s]\n 90%|█████████ | 45/50 [00:15<00:00, 17.30it/s]\n 94%|█████████▍| 47/50 [00:15<00:00, 17.37it/s]\n 98%|█████████▊| 49/50 [00:15<00:00, 17.42it/s]\n100%|██████████| 50/50 [00:15<00:00,  3.26it/s]",
  "metrics": {
    "predict_time": 17.238871525,
    "total_time": 113.157738
  },
  "output": [
    "https://replicate.delivery/pbxt/LvJp7HFVhhIULlRDkZVc2NSA5MI9LDVQue7nNfJYMDkHKODTA/out-0.png"
  ],
  "started_at": "2024-06-28T21:51:51.662866Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/p3343w6wr1rgm0cgc39sh11m7c",
    "cancel": "https://api.replicate.com/v1/predictions/p3343w6wr1rgm0cgc39sh11m7c/cancel"
  },
  "version": "d6659251793b795fca3f80006f36005859c73fdc9d1b112a432a120b1b0ad311"
}

Generated in

17.2 seconds