{
  "model": "dev",
  "prompt": "black rooster in the style of TOK",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 28
}

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

const output = await replicate.run(
  "codingfu/bayc:d111b63dd1444d142fe8a0c0812ce6796e270f05b791d48d2a5c6296627da82a",
  {
    input: {
      model: "dev",
      prompt: "black rooster in the style of TOK",
      lora_scale: 1,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

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

output = replicate.run(
    "codingfu/bayc:d111b63dd1444d142fe8a0c0812ce6796e270f05b791d48d2a5c6296627da82a",
    input={
        "model": "dev",
        "prompt": "black rooster in the style of TOK",
        "lora_scale": 1,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 28
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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

Run codingfu/bayc 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": "codingfu/bayc:d111b63dd1444d142fe8a0c0812ce6796e270f05b791d48d2a5c6296627da82a",
    "input": {
      "model": "dev",
      "prompt": "black rooster in the style of TOK",
      "lora_scale": 1,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-08-22T18:35:53.880687Z",
  "created_at": "2024-08-22T18:35:06.066000Z",
  "data_removed": false,
  "error": null,
  "id": "by3t857kt9rm00chfdfagf0v4r",
  "input": {
    "model": "dev",
    "prompt": "black rooster in the style of TOK",
    "lora_scale": 1,
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 80,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 51857\nPrompt: black rooster in the style of TOK\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9781506404352\nDownloading weights\n2024-08-22T18:35:36Z | INFO  | [ Initiating ] chunk_size=150M dest=/src/weights-cache/6421da47ded8c72a url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar\n2024-08-22T18:35:37Z | INFO  | [ Complete ] dest=/src/weights-cache/6421da47ded8c72a size=\"172 MB\" total_elapsed=1.590s url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar\nb''\nDownloaded weights in 1.6112327575683594 seconds\nLoRA weights loaded successfully\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:07,  3.69it/s]\n  7%|▋         | 2/28 [00:00<00:06,  4.23it/s]\n 11%|█         | 3/28 [00:00<00:06,  3.96it/s]\n 14%|█▍        | 4/28 [00:01<00:06,  3.85it/s]\n 18%|█▊        | 5/28 [00:01<00:06,  3.79it/s]\n 21%|██▏       | 6/28 [00:01<00:05,  3.75it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  3.72it/s]\n 29%|██▊       | 8/28 [00:02<00:05,  3.71it/s]\n 32%|███▏      | 9/28 [00:02<00:05,  3.70it/s]\n 36%|███▌      | 10/28 [00:02<00:04,  3.69it/s]\n 39%|███▉      | 11/28 [00:02<00:04,  3.69it/s]\n 43%|████▎     | 12/28 [00:03<00:04,  3.68it/s]\n 46%|████▋     | 13/28 [00:03<00:04,  3.68it/s]\n 50%|█████     | 14/28 [00:03<00:03,  3.68it/s]\n 54%|█████▎    | 15/28 [00:04<00:03,  3.68it/s]\n 57%|█████▋    | 16/28 [00:04<00:03,  3.68it/s]\n 61%|██████    | 17/28 [00:04<00:02,  3.68it/s]\n 64%|██████▍   | 18/28 [00:04<00:02,  3.68it/s]\n 68%|██████▊   | 19/28 [00:05<00:02,  3.68it/s]\n 71%|███████▏  | 20/28 [00:05<00:02,  3.68it/s]\n 75%|███████▌  | 21/28 [00:05<00:01,  3.68it/s]\n 79%|███████▊  | 22/28 [00:05<00:01,  3.68it/s]\n 82%|████████▏ | 23/28 [00:06<00:01,  3.68it/s]\n 86%|████████▌ | 24/28 [00:06<00:01,  3.68it/s]\n 89%|████████▉ | 25/28 [00:06<00:00,  3.68it/s]\n 93%|█████████▎| 26/28 [00:07<00:00,  3.68it/s]\n 96%|█████████▋| 27/28 [00:07<00:00,  3.68it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.68it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.71it/s]",
  "metrics": {
    "predict_time": 17.844050377,
    "total_time": 47.814687
  },
  "output": [
    "https://replicate.delivery/yhqm/f4be162dhUlzMEXKUSUnaqOw2OYue0g9efxLjGitpJjLhbqaC/out-0.webp"
  ],
  "started_at": "2024-08-22T18:35:36.036636Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/by3t857kt9rm00chfdfagf0v4r",
    "cancel": "https://api.replicate.com/v1/predictions/by3t857kt9rm00chfdfagf0v4r/cancel"
  },
  "version": "d111b63dd1444d142fe8a0c0812ce6796e270f05b791d48d2a5c6296627da82a"
}

Generated in

17.9 seconds

Tweak it Iterate in playground Share Report

Using seed: 51857
Prompt: black rooster in the style of TOK
txt2img mode
Using dev model
Loading LoRA weights
Ensuring enough disk space...
Free disk space: 9781506404352
Downloading weights
2024-08-22T18:35:36Z | INFO  | [ Initiating ] chunk_size=150M dest=/src/weights-cache/6421da47ded8c72a url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar
2024-08-22T18:35:37Z | INFO  | [ Complete ] dest=/src/weights-cache/6421da47ded8c72a size="172 MB" total_elapsed=1.590s url=https://replicate.delivery/yhqm/0jDnFOgloXY9IpHvsM82mSKLWxkt59uYkc3CketKvQ7dtpqJA/trained_model.tar
b''
Downloaded weights in 1.6112327575683594 seconds
LoRA weights loaded successfully
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Want to make some of these yourself?

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