22-hours/vintedois-diffusion:28cea91b – Run with an API on Replicate

Version

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22-hours /vintedois-diffusion:28cea91b

Input

prompt

string

Shift + Return to add a new line

photo of an old man in a jungle, looking at the cameraphoto of an old man in a jungle, looking at the camera

Input prompt

Default: "a photo of an astronaut riding a horse on mars"

negative_prompt

string

Shift + Return to add a new line

Specify things to not see in the output

width

integer

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

Default: 640

height

integer

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

Default: 640

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: "K_EULER_ANCESTRAL"

seed

integer

Random seed. Leave blank to randomize the seed

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

npx create-replicate --model=22-hours/vintedois-diffusion

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 22-hours/vintedois-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "22-hours/vintedois-diffusion:28cea91bdfced0e2dc7fda466cc0a46501c0edc84905b2120ea02e0707b967fd",
  {
    input: {
      seed: 44,
      width: 640,
      height: 640,
      prompt: "photo of an old man in a jungle, looking at the camera",
      scheduler: "K_EULER_ANCESTRAL",
      num_outputs: 1,
      guidance_scale: 7.5,
      prompt_strength: 1,
      num_inference_steps: 30
    }
  }
);
console.log(output);

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 22-hours/vintedois-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "22-hours/vintedois-diffusion:28cea91bdfced0e2dc7fda466cc0a46501c0edc84905b2120ea02e0707b967fd",
    input={
        "seed": 44,
        "width": 640,
        "height": 640,
        "prompt": "photo of an old man in a jungle, looking at the camera",
        "scheduler": "K_EULER_ANCESTRAL",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "prompt_strength": 1,
        "num_inference_steps": 30
    }
)
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 22-hours/vintedois-diffusion 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": "28cea91bdfced0e2dc7fda466cc0a46501c0edc84905b2120ea02e0707b967fd",
    "input": {
      "seed": 44,
      "width": 640,
      "height": 640,
      "prompt": "photo of an old man in a jungle, looking at the camera",
      "scheduler": "K_EULER_ANCESTRAL",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "prompt_strength": 1,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-02-08T20:38:36.199682Z",
  "created_at": "2023-02-08T20:35:18.006974Z",
  "data_removed": false,
  "error": null,
  "id": "p4cfg5sk4re4fc7nzxy4d46duq",
  "input": {
    "seed": 44,
    "width": 640,
    "height": 640,
    "prompt": "photo of an old man in a jungle, looking at the camera",
    "scheduler": "K_EULER_ANCESTRAL",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "prompt_strength": 1,
    "num_inference_steps": "30"
  },
  "logs": "Using seed: 44\n  0%|          | 0/30 [00:00<?, ?it/s]\n  3%|▎         | 1/30 [00:02<01:05,  2.25s/it]\n  7%|▋         | 2/30 [00:03<00:41,  1.47s/it]\n 10%|█         | 3/30 [00:04<00:33,  1.22s/it]\n 13%|█▎        | 4/30 [00:05<00:28,  1.11s/it]\n 17%|█▋        | 5/30 [00:05<00:26,  1.04s/it]\n 20%|██        | 6/30 [00:06<00:24,  1.00s/it]\n 23%|██▎       | 7/30 [00:07<00:22,  1.02it/s]\n 27%|██▋       | 8/30 [00:08<00:21,  1.04it/s]\n 30%|███       | 9/30 [00:09<00:20,  1.05it/s]\n 33%|███▎      | 10/30 [00:10<00:18,  1.06it/s]\n 37%|███▋      | 11/30 [00:11<00:17,  1.06it/s]\n 40%|████      | 12/30 [00:12<00:16,  1.06it/s]\n 43%|████▎     | 13/30 [00:13<00:15,  1.07it/s]\n 47%|████▋     | 14/30 [00:14<00:14,  1.07it/s]\n 50%|█████     | 15/30 [00:15<00:14,  1.07it/s]\n 53%|█████▎    | 16/30 [00:16<00:13,  1.06it/s]\n 57%|█████▋    | 17/30 [00:17<00:12,  1.06it/s]\n 60%|██████    | 18/30 [00:18<00:11,  1.06it/s]\n 63%|██████▎   | 19/30 [00:19<00:10,  1.06it/s]\n 67%|██████▋   | 20/30 [00:19<00:09,  1.06it/s]\n 70%|███████   | 21/30 [00:20<00:08,  1.06it/s]\n 73%|███████▎  | 22/30 [00:21<00:07,  1.06it/s]\n 77%|███████▋  | 23/30 [00:22<00:06,  1.06it/s]\n 80%|████████  | 24/30 [00:23<00:05,  1.06it/s]\n 83%|████████▎ | 25/30 [00:24<00:04,  1.06it/s]\n 87%|████████▋ | 26/30 [00:25<00:03,  1.06it/s]\n 90%|█████████ | 27/30 [00:26<00:02,  1.06it/s]\n 93%|█████████▎| 28/30 [00:27<00:01,  1.06it/s]\n 97%|█████████▋| 29/30 [00:28<00:00,  1.06it/s]\n100%|██████████| 30/30 [00:29<00:00,  1.06it/s]\n100%|██████████| 30/30 [00:29<00:00,  1.02it/s]",
  "metrics": {
    "predict_time": 33.138677,
    "total_time": 198.192708
  },
  "output": [
    "https://replicate.delivery/pbxt/VocmoncW6vafIqTpQnvGJfatWKRUrUggOEdujApt6JpLpbcQA/out-0.png"
  ],
  "started_at": "2023-02-08T20:38:03.061005Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/p4cfg5sk4re4fc7nzxy4d46duq",
    "cancel": "https://api.replicate.com/v1/predictions/p4cfg5sk4re4fc7nzxy4d46duq/cancel"
  },
  "version": "28cea91bdfced0e2dc7fda466cc0a46501c0edc84905b2120ea02e0707b967fd"
}

Generated in

33.1 seconds

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