Prediction

Model

stability-ai/stable-diffusion:8abccf52

rsytjp72cbghhh7gr4ax4rnwly

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

4.2s

Created

about 3 years ago by bfirsh

Webhook

–

Input

prompt: multicolor hyperspace
width: 512
height: 512
prompt_strength: 0.8
num_outputs: 1
num_inference_steps: 50
guidance_scale: 7.5
scheduler: K-LMS

{
  "guidance_scale": 7.5,
  "height": 512,
  "num_inference_steps": 50,
  "num_outputs": "1",
  "prompt": "multicolor hyperspace",
  "prompt_strength": 0.8,
  "scheduler": "K-LMS",
  "width": 512
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_CDQ**********************************

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 stability-ai/stable-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "stability-ai/stable-diffusion:8abccf52e7cba9f6e82317253f4a3549082e966db5584e92c808ece132037776",
  {
    input: {
      guidance_scale: 7.5,
      height: 512,
      num_inference_steps: 50,
      num_outputs: "1",
      prompt: "multicolor hyperspace",
      prompt_strength: 0.8,
      scheduler: "K-LMS",
      width: 512
    }
  }
);

// 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_CDQ**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run stability-ai/stable-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "stability-ai/stable-diffusion:8abccf52e7cba9f6e82317253f4a3549082e966db5584e92c808ece132037776",
    input={
        "guidance_scale": 7.5,
        "height": 512,
        "num_inference_steps": 50,
        "num_outputs": "1",
        "prompt": "multicolor hyperspace",
        "prompt_strength": 0.8,
        "scheduler": "K-LMS",
        "width": 512
    }
)

# 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_CDQ**********************************

This is your API token. Keep it to yourself.

Run stability-ai/stable-diffusion 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": "stability-ai/stable-diffusion:8abccf52e7cba9f6e82317253f4a3549082e966db5584e92c808ece132037776",
    "input": {
      "guidance_scale": 7.5,
      "height": 512,
      "num_inference_steps": 50,
      "num_outputs": "1",
      "prompt": "multicolor hyperspace",
      "prompt_strength": 0.8,
      "scheduler": "K-LMS",
      "width": 512
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "rsytjp72cbghhh7gr4ax4rnwly",
  "model": "stability-ai/stable-diffusion",
  "version": "8abccf52e7cba9f6e82317253f4a3549082e966db5584e92c808ece132037776",
  "input": {
    "guidance_scale": 7.5,
    "height": 512,
    "num_inference_steps": 50,
    "num_outputs": "1",
    "prompt": "multicolor hyperspace",
    "prompt_strength": 0.8,
    "scheduler": "K-LMS",
    "width": 512
  },
  "logs": "Using seed: 45688\n\n  0%|          | 0/50 [00:00<?, ?it/s]\n  2%|▏         | 1/50 [00:00<00:05,  9.47it/s]\n  6%|▌         | 3/50 [00:00<00:03, 12.33it/s]\n 10%|█         | 5/50 [00:00<00:03, 12.32it/s]\n 14%|█▍        | 7/50 [00:00<00:03, 12.99it/s]\n 18%|█▊        | 9/50 [00:00<00:03, 13.40it/s]\n 22%|██▏       | 11/50 [00:00<00:02, 13.62it/s]\n 26%|██▌       | 13/50 [00:00<00:02, 13.30it/s]\n 30%|███       | 15/50 [00:01<00:02, 13.48it/s]\n 34%|███▍      | 17/50 [00:01<00:02, 13.55it/s]\n 38%|███▊      | 19/50 [00:01<00:02, 13.66it/s]\n 42%|████▏     | 21/50 [00:01<00:02, 13.75it/s]\n 46%|████▌     | 23/50 [00:01<00:01, 13.76it/s]\n 50%|█████     | 25/50 [00:01<00:01, 13.35it/s]\n 54%|█████▍    | 27/50 [00:02<00:01, 13.50it/s]\n 58%|█████▊    | 29/50 [00:02<00:01, 13.60it/s]\n 62%|██████▏   | 31/50 [00:02<00:01, 13.69it/s]\n 66%|██████▌   | 33/50 [00:02<00:01, 13.74it/s]\n 70%|███████   | 35/50 [00:02<00:01, 13.78it/s]\n 74%|███████▍  | 37/50 [00:02<00:00, 13.46it/s]\n 78%|███████▊  | 39/50 [00:02<00:00, 13.57it/s]\n 82%|████████▏ | 41/50 [00:03<00:00, 13.60it/s]\n 86%|████████▌ | 43/50 [00:03<00:00, 13.68it/s]\n 90%|█████████ | 45/50 [00:03<00:00, 13.63it/s]\n 94%|█████████▍| 47/50 [00:03<00:00, 13.73it/s]\n 98%|█████████▊| 49/50 [00:03<00:00, 13.65it/s]\n100%|██████████| 50/50 [00:03<00:00, 13.49it/s]",
  "output": [
    "https://replicate.delivery/pbxt/Uy5Ma1EruBKkOReB5TwrX9P1ekJjnSftkujvBqkDneSCMywfB/out-0.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2022-11-03T01:17:48.71892Z",
  "started_at": "2022-11-03T01:17:48.752863Z",
  "completed_at": "2022-11-03T01:17:52.861177Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/rsytjp72cbghhh7gr4ax4rnwly/cancel",
    "get": "https://api.replicate.com/v1/predictions/rsytjp72cbghhh7gr4ax4rnwly"
  },
  "metrics": {
    "predict_time": 4.108314,
    "total_time": 4.142257
  }
}

Generated in

4.1 seconds

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