Prediction

Model

jyoung105/playground-v2.5:5fda9802

0njdga6cexrgp0ck8c0r47xk4w

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

2m 58s

Created

about 1 year ago

Webhook

–

Input

prompt: A man with hoodie on, illustration
width: 1024
height: 1024
num_images: 1
steps: 25
eta: 0
guidance_scale: 3
clip_skip: 0

{
  "clip_skip": 0,
  "eta": 0,
  "guidance_scale": 3,
  "height": 1024,
  "num_images": 1,
  "prompt": "A man with hoodie on, illustration",
  "steps": 25,
  "width": 1024
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_ENX**********************************

This is your API token. Keep it to yourself.

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 jyoung105/playground-v2.5 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jyoung105/playground-v2.5:5fda98020af104f265d61b52bfb5ce4b2e3987e3d94cb61a6997bf009454fddf",
  {
    input: {
      clip_skip: 0,
      eta: 0,
      guidance_scale: 3,
      height: 1024,
      num_images: 1,
      prompt: "A man with hoodie on, illustration",
      steps: 25,
      width: 1024
    }
  }
);

// 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=r8_ENX**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run jyoung105/playground-v2.5 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jyoung105/playground-v2.5:5fda98020af104f265d61b52bfb5ce4b2e3987e3d94cb61a6997bf009454fddf",
    input={
        "clip_skip": 0,
        "eta": 0,
        "guidance_scale": 3,
        "height": 1024,
        "num_images": 1,
        "prompt": "A man with hoodie on, illustration",
        "steps": 25,
        "width": 1024
    }
)

# 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.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_ENX**********************************

This is your API token. Keep it to yourself.

Run jyoung105/playground-v2.5 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": "jyoung105/playground-v2.5:5fda98020af104f265d61b52bfb5ce4b2e3987e3d94cb61a6997bf009454fddf",
    "input": {
      "clip_skip": 0,
      "eta": 0,
      "guidance_scale": 3,
      "height": 1024,
      "num_images": 1,
      "prompt": "A man with hoodie on, illustration",
      "steps": 25,
      "width": 1024
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "0njdga6cexrgp0ck8c0r47xk4w",
  "model": "jyoung105/playground-v2.5",
  "version": "5fda98020af104f265d61b52bfb5ce4b2e3987e3d94cb61a6997bf009454fddf",
  "input": {
    "clip_skip": 0,
    "eta": 0,
    "guidance_scale": 3,
    "height": 1024,
    "num_images": 1,
    "prompt": "A man with hoodie on, illustration",
    "steps": 25,
    "width": 1024
  },
  "logs": "[Debug] DEVICE: cuda\n[Debug] DTYPE: torch.float16\nSetup completed in 0.00 seconds.\n[~] Generating images...\n[Debug] Prompt: A man with hoodie on, illustration, best quality, high detail, sharp focus\n[Debug] Seed: 53071\n  0%|          | 0/25 [00:00<?, ?it/s]\n  4%|▍         | 1/25 [00:01<00:31,  1.30s/it]\n 12%|█▏        | 3/25 [00:01<00:09,  2.29it/s]\n 16%|█▌        | 4/25 [00:01<00:07,  2.84it/s]\n 20%|██        | 5/25 [00:01<00:05,  3.35it/s]\n 24%|██▍       | 6/25 [00:02<00:05,  3.79it/s]\n 28%|██▊       | 7/25 [00:02<00:04,  4.12it/s]\n 32%|███▏      | 8/25 [00:02<00:03,  4.41it/s]\n 36%|███▌      | 9/25 [00:02<00:03,  4.63it/s]\n 40%|████      | 10/25 [00:02<00:03,  4.80it/s]\n 44%|████▍     | 11/25 [00:03<00:02,  4.92it/s]\n 48%|████▊     | 12/25 [00:03<00:02,  4.98it/s]\n 52%|█████▏    | 13/25 [00:03<00:02,  5.05it/s]\n 56%|█████▌    | 14/25 [00:03<00:02,  5.09it/s]\n 60%|██████    | 15/25 [00:03<00:01,  5.13it/s]\n 64%|██████▍   | 16/25 [00:04<00:01,  5.15it/s]\n 68%|██████▊   | 17/25 [00:04<00:01,  5.16it/s]\n 72%|███████▏  | 18/25 [00:04<00:01,  5.17it/s]\n 76%|███████▌  | 19/25 [00:04<00:01,  5.18it/s]\n 80%|████████  | 20/25 [00:04<00:00,  5.18it/s]\n 84%|████████▍ | 21/25 [00:05<00:00,  5.19it/s]\n 88%|████████▊ | 22/25 [00:05<00:00,  5.18it/s]\n 92%|█████████▏| 23/25 [00:05<00:00,  5.18it/s]\n 96%|█████████▌| 24/25 [00:05<00:00,  5.18it/s]\n100%|██████████| 25/25 [00:05<00:00,  5.19it/s]\n100%|██████████| 25/25 [00:05<00:00,  4.31it/s]\nImage generation completed in 7.10 seconds.",
  "output": [
    "https://replicate.delivery/pbxt/fMnI1LfuKnnPJUAyVaaiffN6PbfesZMSFVdPiMH6GZ6IHcn8E/out_0.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-11-19T06:00:11.639Z",
  "started_at": "2024-11-19T06:03:00.938116Z",
  "completed_at": "2024-11-19T06:03:09.809417Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/0njdga6cexrgp0ck8c0r47xk4w/cancel",
    "get": "https://api.replicate.com/v1/predictions/0njdga6cexrgp0ck8c0r47xk4w",
    "web": "https://replicate.com/p/0njdga6cexrgp0ck8c0r47xk4w"
  },
  "metrics": {
    "predict_time": 8.871300686,
    "total_time": 178.170417
  }
}

Generated in

8.9 seconds

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