Prediction

Model

ai-forever/kandinsky-2:601eea49

ztcjz6rbbyoyzrfmjuazttrq3a

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

12.9s

Created

over 2 years ago by janbletz

Webhook

–

Input

prompt: old cow based on the pink floyd album atom heart mother
num_inference_steps: 100
guidance_scale: 4
scheduler: p_sampler
prior_cf_scale: 4
prior_steps: 5
width: 768
height: 768
batch_size: 1

{
  "batch_size": 1,
  "guidance_scale": 4,
  "height": "768",
  "num_inference_steps": 100,
  "prior_cf_scale": 4,
  "prior_steps": "5",
  "prompt": "old cow based on the pink floyd album atom heart mother",
  "scheduler": "p_sampler",
  "width": "768"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_K21**********************************

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 ai-forever/kandinsky-2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ai-forever/kandinsky-2:601eea49d49003e6ea75a11527209c4f510a93e2112c969d548fbb45b9c4f19f",
  {
    input: {
      batch_size: 1,
      guidance_scale: 4,
      height: "768",
      num_inference_steps: 100,
      prior_cf_scale: 4,
      prior_steps: "5",
      prompt: "old cow based on the pink floyd album atom heart mother",
      scheduler: "p_sampler",
      width: "768"
    }
  }
);

// 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_K21**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run ai-forever/kandinsky-2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ai-forever/kandinsky-2:601eea49d49003e6ea75a11527209c4f510a93e2112c969d548fbb45b9c4f19f",
    input={
        "batch_size": 1,
        "guidance_scale": 4,
        "height": "768",
        "num_inference_steps": 100,
        "prior_cf_scale": 4,
        "prior_steps": "5",
        "prompt": "old cow based on the pink floyd album atom heart mother",
        "scheduler": "p_sampler",
        "width": "768"
    }
)

# 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_K21**********************************

This is your API token. Keep it to yourself.

Run ai-forever/kandinsky-2 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": "ai-forever/kandinsky-2:601eea49d49003e6ea75a11527209c4f510a93e2112c969d548fbb45b9c4f19f",
    "input": {
      "batch_size": 1,
      "guidance_scale": 4,
      "height": "768",
      "num_inference_steps": 100,
      "prior_cf_scale": 4,
      "prior_steps": "5",
      "prompt": "old cow based on the pink floyd album atom heart mother",
      "scheduler": "p_sampler",
      "width": "768"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "ztcjz6rbbyoyzrfmjuazttrq3a",
  "model": "ai-forever/kandinsky-2",
  "version": "601eea49d49003e6ea75a11527209c4f510a93e2112c969d548fbb45b9c4f19f",
  "input": {
    "batch_size": 1,
    "guidance_scale": 4,
    "height": "768",
    "num_inference_steps": 100,
    "prior_cf_scale": 4,
    "prior_steps": "5",
    "prompt": "old cow based on the pink floyd album atom heart mother",
    "scheduler": "p_sampler",
    "width": "768"
  },
  "logs": "0%|          | 0/100 [00:00<?, ?it/s]\n  1%|          | 1/100 [00:00<00:13,  7.11it/s]\n  3%|▎         | 3/100 [00:00<00:09,  9.83it/s]\n  5%|▌         | 5/100 [00:00<00:09, 10.51it/s]\n  7%|▋         | 7/100 [00:00<00:08, 10.87it/s]\n  9%|▉         | 9/100 [00:00<00:08, 11.06it/s]\n 11%|█         | 11/100 [00:01<00:08, 11.05it/s]\n 13%|█▎        | 13/100 [00:01<00:08, 10.87it/s]\n 15%|█▌        | 15/100 [00:01<00:07, 10.99it/s]\n 17%|█▋        | 17/100 [00:01<00:07, 11.08it/s]\n 19%|█▉        | 19/100 [00:01<00:07, 11.16it/s]\n 21%|██        | 21/100 [00:01<00:07, 11.17it/s]\n 23%|██▎       | 23/100 [00:02<00:06, 11.16it/s]\n 25%|██▌       | 25/100 [00:02<00:06, 11.19it/s]\n 27%|██▋       | 27/100 [00:02<00:06, 11.24it/s]\n 29%|██▉       | 29/100 [00:02<00:06, 11.21it/s]\n 31%|███       | 31/100 [00:02<00:06, 11.25it/s]\n 33%|███▎      | 33/100 [00:03<00:06, 11.06it/s]\n 35%|███▌      | 35/100 [00:03<00:05, 11.06it/s]\n 37%|███▋      | 37/100 [00:03<00:05, 11.17it/s]\n 39%|███▉      | 39/100 [00:03<00:05, 11.24it/s]\n 41%|████      | 41/100 [00:03<00:05, 11.24it/s]\n 43%|████▎     | 43/100 [00:03<00:05, 11.11it/s]\n 45%|████▌     | 45/100 [00:04<00:04, 11.06it/s]\n 47%|████▋     | 47/100 [00:04<00:04, 11.05it/s]\n 49%|████▉     | 49/100 [00:04<00:04, 11.09it/s]\n 51%|█████     | 51/100 [00:04<00:04, 11.14it/s]\n 53%|█████▎    | 53/100 [00:04<00:04, 11.19it/s]\n 55%|█████▌    | 55/100 [00:04<00:04, 11.18it/s]\n 57%|█████▋    | 57/100 [00:05<00:03, 11.15it/s]\n 59%|█████▉    | 59/100 [00:05<00:03, 11.19it/s]\n 61%|██████    | 61/100 [00:05<00:03, 11.23it/s]\n 63%|██████▎   | 63/100 [00:05<00:03, 11.25it/s]\n 65%|██████▌   | 65/100 [00:05<00:03, 11.29it/s]\n 67%|██████▋   | 67/100 [00:06<00:02, 11.19it/s]\n 69%|██████▉   | 69/100 [00:06<00:02, 11.22it/s]\n 71%|███████   | 71/100 [00:06<00:02, 11.22it/s]\n 73%|███████▎  | 73/100 [00:06<00:02, 11.25it/s]\n 75%|███████▌  | 75/100 [00:06<00:02, 11.28it/s]\n 77%|███████▋  | 77/100 [00:06<00:02, 11.08it/s]\n 79%|███████▉  | 79/100 [00:07<00:01, 11.06it/s]\n 81%|████████  | 81/100 [00:07<00:01, 11.11it/s]\n 83%|████████▎ | 83/100 [00:07<00:01, 11.15it/s]\n 85%|████████▌ | 85/100 [00:07<00:01, 11.17it/s]\n 87%|████████▋ | 87/100 [00:07<00:01, 11.20it/s]\n 89%|████████▉ | 89/100 [00:08<00:00, 11.21it/s]\n 91%|█████████ | 91/100 [00:08<00:00, 11.28it/s]\n 93%|█████████▎| 93/100 [00:08<00:00, 11.34it/s]\n 95%|█████████▌| 95/100 [00:08<00:00, 11.39it/s]\n 97%|█████████▋| 97/100 [00:08<00:00, 11.35it/s]\n 99%|█████████▉| 99/100 [00:08<00:00, 11.39it/s]\n100%|██████████| 100/100 [00:08<00:00, 11.14it/s]",
  "output": [
    "https://replicate.delivery/pbxt/fN2T8Opk14TKUyyFuFZrg8AFGsSHrmKeNIBkoPC23yzaTtLRA/out_0.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-07-02T07:10:06.637564Z",
  "started_at": "2023-07-02T07:10:08.92481Z",
  "completed_at": "2023-07-02T07:10:19.498911Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/ztcjz6rbbyoyzrfmjuazttrq3a/cancel",
    "get": "https://api.replicate.com/v1/predictions/ztcjz6rbbyoyzrfmjuazttrq3a"
  },
  "metrics": {
    "predict_time": 10.574101,
    "total_time": 12.861347
  }
}

Generated in

10.6 seconds

Tweak it Report

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