Prediction

Model

ai-forever/kandinsky-2:9c0bf7d5

wixq75uo65glnjcdgrqtngdz4q

Status

Succeeded

Source

Web

Hardware

–

Total duration

71.6s

Created

over 2 years ago by chenxwh

Webhook

–

Input

prompt: red cat, 4k photo
num_inference_steps: 100
guidance_scale: 4
scheduler: p_sampler
prior_cf_scale: 4
prior_steps: 5

{
  "guidance_scale": 4,
  "num_inference_steps": 100,
  "prior_cf_scale": 4,
  "prior_steps": "5",
  "prompt": "red cat, 4k photo",
  "scheduler": "p_sampler"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_HWW**********************************

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-2:9c0bf7d5cf2ed934c5921faf61882657c03c4def9d9cb88330c15bd795edb098",
  {
    input: {
      guidance_scale: 4,
      num_inference_steps: 100,
      prior_cf_scale: 4,
      prior_steps: "5",
      prompt: "red cat, 4k photo",
      scheduler: "p_sampler"
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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=r8_HWW**********************************

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-2:9c0bf7d5cf2ed934c5921faf61882657c03c4def9d9cb88330c15bd795edb098",
    input={
        "guidance_scale": 4,
        "num_inference_steps": 100,
        "prior_cf_scale": 4,
        "prior_steps": "5",
        "prompt": "red cat, 4k photo",
        "scheduler": "p_sampler"
    }
)

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

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.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_HWW**********************************

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-2:9c0bf7d5cf2ed934c5921faf61882657c03c4def9d9cb88330c15bd795edb098",
    "input": {
      "guidance_scale": 4,
      "num_inference_steps": 100,
      "prior_cf_scale": 4,
      "prior_steps": "5",
      "prompt": "red cat, 4k photo",
      "scheduler": "p_sampler"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "wixq75uo65glnjcdgrqtngdz4q",
  "model": "ai-forever/kandinsky-2",
  "version": "9c0bf7d5cf2ed934c5921faf61882657c03c4def9d9cb88330c15bd795edb098",
  "input": {
    "guidance_scale": 4,
    "num_inference_steps": 100,
    "prior_cf_scale": 4,
    "prior_steps": "5",
    "prompt": "red cat, 4k photo",
    "scheduler": "p_sampler"
  },
  "logs": "0%|          | 0/100 [00:00<?, ?it/s]\n  1%|          | 1/100 [00:00<01:21,  1.21it/s]\n  2%|▏         | 2/100 [00:01<01:08,  1.42it/s]\n  3%|▎         | 3/100 [00:02<01:04,  1.51it/s]\n  4%|▍         | 4/100 [00:02<01:02,  1.54it/s]\n  5%|▌         | 5/100 [00:03<01:00,  1.56it/s]\n  6%|▌         | 6/100 [00:03<01:00,  1.57it/s]\n  7%|▋         | 7/100 [00:04<00:59,  1.57it/s]\n  8%|▊         | 8/100 [00:05<00:58,  1.58it/s]\n  9%|▉         | 9/100 [00:05<00:57,  1.58it/s]\n 10%|█         | 10/100 [00:06<00:56,  1.58it/s]\n 11%|█         | 11/100 [00:07<00:56,  1.58it/s]\n 12%|█▏        | 12/100 [00:07<00:55,  1.58it/s]\n 13%|█▎        | 13/100 [00:08<00:54,  1.59it/s]\n 14%|█▍        | 14/100 [00:08<00:54,  1.58it/s]\n 15%|█▌        | 15/100 [00:09<00:53,  1.58it/s]\n 16%|█▌        | 16/100 [00:10<00:53,  1.58it/s]\n 17%|█▋        | 17/100 [00:10<00:52,  1.59it/s]\n 18%|█▊        | 18/100 [00:11<00:51,  1.59it/s]\n 19%|█▉        | 19/100 [00:12<00:51,  1.59it/s]\n 20%|██   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  "output": "https://replicate.delivery/pbxt/NsOpfQRos43e40IzSq4SY7NTtxGodmSWo1m74K17SVpoUzuQA/out.png",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-04-05T14:17:05.82402Z",
  "started_at": "2023-04-05T14:17:06.118097Z",
  "completed_at": "2023-04-05T14:18:17.379573Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/wixq75uo65glnjcdgrqtngdz4q/cancel",
    "get": "https://api.replicate.com/v1/predictions/wixq75uo65glnjcdgrqtngdz4q"
  },
  "metrics": {
    "predict_time": 71.261476,
    "total_time": 71.555553
  }
}

Generated in

71.3 seconds

Tweak it Report

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