delta-lock / ponynai3

{
  "vae": "default",
  "seed": -1,
  "model": "tPonynai3_v7",
  "steps": 35,
  "width": 1184,
  "height": 864,
  "prompt": "1girl",
  "strength": 0.7,
  "cfg_scale": 5,
  "clip_skip": 1,
  "pag_scale": 3,
  "scheduler": "Euler a",
  "batch_size": 1,
  "blur_factor": 5,
  "negative_prompt": "animal, cat, dog, big breasts",
  "guidance_rescale": 0.5,
  "prepend_preprompt": true
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run delta-lock/ponynai3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "delta-lock/ponynai3:848da0d3e5a762b8662592acd1818003a3b4672f513d7250895bd0d96c6a48c9",
  {
    input: {
      vae: "default",
      seed: -1,
      model: "tPonynai3_v7",
      steps: 35,
      width: 1184,
      height: 864,
      prompt: "1girl",
      strength: 0.7,
      cfg_scale: 5,
      clip_skip: 1,
      pag_scale: 3,
      scheduler: "Euler a",
      batch_size: 1,
      blur_factor: 5,
      negative_prompt: "animal, cat, dog, big breasts",
      guidance_rescale: 0.5,
      prepend_preprompt: true
    }
  }
);

// 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 delta-lock/ponynai3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "delta-lock/ponynai3:848da0d3e5a762b8662592acd1818003a3b4672f513d7250895bd0d96c6a48c9",
    input={
        "vae": "default",
        "seed": -1,
        "model": "tPonynai3_v7",
        "steps": 35,
        "width": 1184,
        "height": 864,
        "prompt": "1girl",
        "strength": 0.7,
        "cfg_scale": 5,
        "clip_skip": 1,
        "pag_scale": 3,
        "scheduler": "Euler a",
        "batch_size": 1,
        "blur_factor": 5,
        "negative_prompt": "animal, cat, dog, big breasts",
        "guidance_rescale": 0.5,
        "prepend_preprompt": True
    }
)
print(output)

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

Run delta-lock/ponynai3 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": "delta-lock/ponynai3:848da0d3e5a762b8662592acd1818003a3b4672f513d7250895bd0d96c6a48c9",
    "input": {
      "vae": "default",
      "seed": -1,
      "model": "tPonynai3_v7",
      "steps": 35,
      "width": 1184,
      "height": 864,
      "prompt": "1girl",
      "strength": 0.7,
      "cfg_scale": 5,
      "clip_skip": 1,
      "pag_scale": 3,
      "scheduler": "Euler a",
      "batch_size": 1,
      "blur_factor": 5,
      "negative_prompt": "animal, cat, dog, big breasts",
      "guidance_rescale": 0.5,
      "prepend_preprompt": true
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/delta-lock/ponynai3@sha256:848da0d3e5a762b8662592acd1818003a3b4672f513d7250895bd0d96c6a48c9 \
  -i 'vae="default"' \
  -i 'seed=-1' \
  -i 'model="tPonynai3_v7"' \
  -i 'steps=35' \
  -i 'width=1184' \
  -i 'height=864' \
  -i 'prompt="1girl"' \
  -i 'strength=0.7' \
  -i 'cfg_scale=5' \
  -i 'clip_skip=1' \
  -i 'pag_scale=3' \
  -i 'scheduler="Euler a"' \
  -i 'batch_size=1' \
  -i 'blur_factor=5' \
  -i 'negative_prompt="animal, cat, dog, big breasts"' \
  -i 'guidance_rescale=0.5' \
  -i 'prepend_preprompt=true'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/delta-lock/ponynai3@sha256:848da0d3e5a762b8662592acd1818003a3b4672f513d7250895bd0d96c6a48c9
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "vae": "default",
      "seed": -1,
      "model": "tPonynai3_v7",
      "steps": 35,
      "width": 1184,
      "height": 864,
      "prompt": "1girl",
      "strength": 0.7,
      "cfg_scale": 5,
      "clip_skip": 1,
      "pag_scale": 3,
      "scheduler": "Euler a",
      "batch_size": 1,
      "blur_factor": 5,
      "negative_prompt": "animal, cat, dog, big breasts",
      "guidance_rescale": 0.5,
      "prepend_preprompt": true
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2025-05-11T10:55:47.000294Z",
  "created_at": "2025-05-11T10:53:38.905000Z",
  "data_removed": false,
  "error": null,
  "id": "gc73rwn2v5rmc0cpqvxad1ep18",
  "input": {
    "vae": "default",
    "seed": -1,
    "model": "tPonynai3_v7",
    "steps": 35,
    "width": 1184,
    "height": 864,
    "prompt": "1girl",
    "strength": 0.7,
    "cfg_scale": 5,
    "clip_skip": 1,
    "pag_scale": 3,
    "scheduler": "Euler a",
    "batch_size": 1,
    "blur_factor": 5,
    "negative_prompt": "animal, cat, dog, big breasts",
    "guidance_rescale": 0.5,
    "prepend_preprompt": true
  },
  "logs": "Using text to image mode.\nUsing seed: 421887767\n  0%|          | 0/35 [00:00<?, ?it/s]\n  3%|▎         | 1/35 [00:00<00:08,  4.21it/s]\n  9%|▊         | 3/35 [00:00<00:04,  7.09it/s]\n 11%|█▏        | 4/35 [00:00<00:04,  7.01it/s]\n 14%|█▍        | 5/35 [00:00<00:04,  6.97it/s]\n 17%|█▋        | 6/35 [00:00<00:04,  6.93it/s]\n 20%|██        | 7/35 [00:01<00:04,  6.89it/s]\n 23%|██▎       | 8/35 [00:01<00:03,  6.87it/s]\n 26%|██▌       | 9/35 [00:01<00:03,  6.86it/s]\n 29%|██▊       | 10/35 [00:01<00:03,  6.85it/s]\n 31%|███▏      | 11/35 [00:01<00:03,  6.84it/s]\n 34%|███▍      | 12/35 [00:01<00:03,  6.82it/s]\n 37%|███▋      | 13/35 [00:01<00:03,  6.82it/s]\n 40%|████      | 14/35 [00:02<00:03,  6.83it/s]\n 43%|████▎     | 15/35 [00:02<00:02,  6.81it/s]\n 46%|████▌     | 16/35 [00:02<00:02,  6.80it/s]\n 49%|████▊     | 17/35 [00:02<00:02,  6.80it/s]\n 51%|█████▏    | 18/35 [00:02<00:02,  6.80it/s]\n 54%|█████▍    | 19/35 [00:02<00:02,  6.80it/s]\n 57%|█████▋    | 20/35 [00:02<00:02,  6.80it/s]\n 60%|██████    | 21/35 [00:03<00:02,  6.79it/s]\n 63%|██████▎   | 22/35 [00:03<00:01,  6.78it/s]\n 66%|██████▌   | 23/35 [00:03<00:01,  6.79it/s]\n 69%|██████▊   | 24/35 [00:03<00:01,  6.78it/s]\n 71%|███████▏  | 25/35 [00:03<00:01,  6.78it/s]\n 74%|███████▍  | 26/35 [00:03<00:01,  6.77it/s]\n 77%|███████▋  | 27/35 [00:03<00:01,  6.77it/s]\n 80%|████████  | 28/35 [00:04<00:01,  6.77it/s]\n 83%|████████▎ | 29/35 [00:04<00:00,  6.76it/s]\n 86%|████████▌ | 30/35 [00:04<00:00,  6.76it/s]\n 89%|████████▊ | 31/35 [00:04<00:00,  6.75it/s]\n 91%|█████████▏| 32/35 [00:04<00:00,  6.75it/s]\n 94%|█████████▍| 33/35 [00:04<00:00,  6.74it/s]\n 97%|█████████▋| 34/35 [00:05<00:00,  6.74it/s]\n100%|██████████| 35/35 [00:05<00:00,  6.74it/s]\n100%|██████████| 35/35 [00:05<00:00,  6.77it/s]",
  "metrics": {
    "predict_time": 7.55949215,
    "total_time": 128.095294
  },
  "output": [
    "https://replicate.delivery/xezq/Z0fpC39b1awejU1b0CqGnleieJnyd0p1ZHN7WW0KINJLDNuSB/0.png"
  ],
  "started_at": "2025-05-11T10:55:39.440801Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-j3tpiviwrgh635l2dfeusegomwllkku43hbxoaf7zamfkrnbdcua",
    "get": "https://api.replicate.com/v1/predictions/gc73rwn2v5rmc0cpqvxad1ep18",
    "cancel": "https://api.replicate.com/v1/predictions/gc73rwn2v5rmc0cpqvxad1ep18/cancel"
  },
  "version": "848da0d3e5a762b8662592acd1818003a3b4672f513d7250895bd0d96c6a48c9"
}

Generated in

7.6 seconds

Tweak it ShareReport

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