Prediction

ID

wh6vokpom5falntu7wrpdtpija

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

52.6s

Created

over 2 years ago

Input

prompt: a pirate ship
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "a pirate ship",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "a pirate ship",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "a pirate ship",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "a pirate ship",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:31:31.653724Z",
  "created_at": "2022-11-01T21:30:39.049462Z",
  "data_removed": false,
  "error": null,
  "id": "wh6vokpom5falntu7wrpdtpija",
  "input": {
    "prompt": "a pirate ship",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 44100\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.50it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.33it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.39it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 15.67it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 15.84it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.10it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.28it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 16.42it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.44it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.53it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.35it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.38it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.39it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.50it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.48it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.53it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.54it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.48it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.25it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.38it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.45it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.27it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.43it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.55it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.53it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.29it/s]",
  "metrics": {
    "predict_time": 3.342506,
    "total_time": 52.604262
  },
  "output": [
    "https://replicate.delivery/pbxt/aDKsiBOtzcJ0JVtUbSmwI9asGDasFMLbtoGEdNNjaN7MC9eHA/out-0.png"
  ],
  "started_at": "2022-11-01T21:31:28.311218Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/wh6vokpom5falntu7wrpdtpija",
    "cancel": "https://api.replicate.com/v1/predictions/wh6vokpom5falntu7wrpdtpija/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.4 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

lm6on2he35cjpcgdzxe2jb5mry

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.3s

Created

over 2 years ago

Input

prompt: darth vader
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "darth vader",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "darth vader",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "darth vader",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "darth vader",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:32:50.147312Z",
  "created_at": "2022-11-01T21:32:46.831479Z",
  "data_removed": false,
  "error": null,
  "id": "lm6on2he35cjpcgdzxe2jb5mry",
  "input": {
    "prompt": "darth vader",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 4286\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.59it/s]\n  8%|▊         | 4/51 [00:00<00:02, 15.76it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 16.12it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.40it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.55it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.59it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.65it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.74it/s]\n 35%|███▌      | 18/51 [00:01<00:01, 16.66it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.57it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.59it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.61it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.65it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.63it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.61it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.41it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.27it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.10it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.34it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.47it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.61it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.70it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.71it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.76it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.70it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.51it/s]",
  "metrics": {
    "predict_time": 3.274491,
    "total_time": 3.315833
  },
  "output": [
    "https://replicate.delivery/pbxt/l2eOUzfcaluL201ztZjYLlb9spIaqTbwNnWu0ZIDvCGCK07PA/out-0.png"
  ],
  "started_at": "2022-11-01T21:32:46.872821Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/lm6on2he35cjpcgdzxe2jb5mry",
    "cancel": "https://api.replicate.com/v1/predictions/lm6on2he35cjpcgdzxe2jb5mry/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

nojdnory75acxoed2r7rbcw2cm

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

9.4s

Created

over 2 years ago

Input

prompt: pirates ball room dancing
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "pirates ball room dancing",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "pirates ball room dancing",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "pirates ball room dancing",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "pirates ball room dancing",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:33:23.556173Z",
  "created_at": "2022-11-01T21:33:14.178064Z",
  "data_removed": false,
  "error": null,
  "id": "nojdnory75acxoed2r7rbcw2cm",
  "input": {
    "prompt": "pirates ball room dancing",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 11992\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  2%|▏         | 1/51 [00:02<01:51,  2.22s/it]\n  6%|▌         | 3/51 [00:02<00:30,  1.59it/s]\n 10%|▉         | 5/51 [00:02<00:15,  2.94it/s]\n 14%|█▎        | 7/51 [00:02<00:09,  4.46it/s]\n 18%|█▊        | 9/51 [00:02<00:06,  6.17it/s]\n 22%|██▏       | 11/51 [00:02<00:05,  7.94it/s]\n 25%|██▌       | 13/51 [00:03<00:04,  9.44it/s]\n 29%|██▉       | 15/51 [00:03<00:03, 10.79it/s]\n 33%|███▎      | 17/51 [00:03<00:02, 12.17it/s]\n 37%|███▋      | 19/51 [00:03<00:02, 13.35it/s]\n 41%|████      | 21/51 [00:03<00:02, 14.16it/s]\n 45%|████▌     | 23/51 [00:03<00:01, 14.80it/s]\n 49%|████▉     | 25/51 [00:03<00:01, 15.34it/s]\n 53%|█████▎    | 27/51 [00:03<00:01, 15.71it/s]\n 57%|█████▋    | 29/51 [00:03<00:01, 15.97it/s]\n 61%|██████    | 31/51 [00:04<00:01, 16.21it/s]\n 65%|██████▍   | 33/51 [00:04<00:01, 16.42it/s]\n 69%|██████▊   | 35/51 [00:04<00:00, 16.50it/s]\n 73%|███████▎  | 37/51 [00:04<00:00, 16.41it/s]\n 76%|███████▋  | 39/51 [00:04<00:00, 16.53it/s]\n 80%|████████  | 41/51 [00:04<00:00, 16.00it/s]\n 84%|████████▍ | 43/51 [00:04<00:00, 15.88it/s]\n 88%|████████▊ | 45/51 [00:04<00:00, 16.15it/s]\n 92%|█████████▏| 47/51 [00:05<00:00, 16.23it/s]\n 96%|█████████▌| 49/51 [00:05<00:00, 16.33it/s]\n100%|██████████| 51/51 [00:05<00:00, 16.47it/s]\n100%|██████████| 51/51 [00:05<00:00,  9.60it/s]",
  "metrics": {
    "predict_time": 9.33406,
    "total_time": 9.378109
  },
  "output": [
    "https://replicate.delivery/pbxt/CjKwZOqk6dKOAhO7Jg2fBQeb0hvcAcMbFwY3Ewi5b8ajK07PA/out-0.png"
  ],
  "started_at": "2022-11-01T21:33:14.222113Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/nojdnory75acxoed2r7rbcw2cm",
    "cancel": "https://api.replicate.com/v1/predictions/nojdnory75acxoed2r7rbcw2cm/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

9.3 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

qm3vbusczjfcjoxh7eop3pbn3u

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.5s

Created

over 2 years ago

Input

prompt: a castle on a hilltop
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "a castle on a hilltop",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "a castle on a hilltop",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "a castle on a hilltop",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "a castle on a hilltop",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:34:34.947878Z",
  "created_at": "2022-11-01T21:34:31.462235Z",
  "data_removed": false,
  "error": null,
  "id": "qm3vbusczjfcjoxh7eop3pbn3u",
  "input": {
    "prompt": "a castle on a hilltop",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 7116\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 13.44it/s]\n  8%|▊         | 4/51 [00:00<00:03, 14.92it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.40it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 15.64it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 14.92it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 15.25it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 15.40it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 15.54it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 15.46it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 15.50it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 15.78it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 15.86it/s]\n 51%|█████     | 26/51 [00:01<00:01, 15.72it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 15.89it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 15.98it/s]\n 63%|██████▎   | 32/51 [00:02<00:01, 15.99it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 15.70it/s]\n 71%|███████   | 36/51 [00:02<00:00, 15.95it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.04it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.10it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.11it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.07it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 15.89it/s]\n 94%|█████████▍| 48/51 [00:03<00:00, 16.12it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.09it/s]\n100%|██████████| 51/51 [00:03<00:00, 15.75it/s]",
  "metrics": {
    "predict_time": 3.444566,
    "total_time": 3.485643
  },
  "output": [
    "https://replicate.delivery/pbxt/SKVALeLtabwHSCydeYLHV93ObxEEEn6Aj9VDMXqgyAQqL07PA/out-0.png"
  ],
  "started_at": "2022-11-01T21:34:31.503312Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/qm3vbusczjfcjoxh7eop3pbn3u",
    "cancel": "https://api.replicate.com/v1/predictions/qm3vbusczjfcjoxh7eop3pbn3u/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.5 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

qpp7ibefmzbg3oemi6bmxnqezy

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: guybrush taking a stroll in downtown new york city
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "guybrush taking a stroll in downtown new york city",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "guybrush taking a stroll in downtown new york city",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "guybrush taking a stroll in downtown new york city",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "guybrush taking a stroll in downtown new york city",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:35:18.165425Z",
  "created_at": "2022-11-01T21:35:14.760688Z",
  "data_removed": false,
  "error": null,
  "id": "qpp7ibefmzbg3oemi6bmxnqezy",
  "input": {
    "prompt": "guybrush taking a stroll in downtown new york city",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 52108\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 13.78it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.43it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.51it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 15.55it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 15.88it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.11it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 15.87it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 15.66it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 15.92it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.12it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 15.88it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 15.76it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.03it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.25it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.41it/s]\n 63%|██████▎   | 32/51 [00:02<00:01, 16.58it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.67it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.79it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.82it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.88it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.86it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.73it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.81it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.89it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.97it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.33it/s]",
  "metrics": {
    "predict_time": 3.360899,
    "total_time": 3.404737
  },
  "output": [
    "https://replicate.delivery/pbxt/XGRdCV283mZODdue7jNnP0W0fflgygVG6FQTGOMfgX0bxQvfB/out-0.png"
  ],
  "started_at": "2022-11-01T21:35:14.804526Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/qpp7ibefmzbg3oemi6bmxnqezy",
    "cancel": "https://api.replicate.com/v1/predictions/qpp7ibefmzbg3oemi6bmxnqezy/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.4 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

drfj2ccsk5hijcs27xbwwuftwu

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: the garden of eden
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "the garden of eden",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "the garden of eden",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "the garden of eden",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "the garden of eden",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:36:04.525319Z",
  "created_at": "2022-11-01T21:36:01.119454Z",
  "data_removed": false,
  "error": null,
  "id": "drfj2ccsk5hijcs27xbwwuftwu",
  "input": {
    "prompt": "the garden of eden",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 39459\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 12.89it/s]\n  8%|▊         | 4/51 [00:00<00:03, 14.48it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.48it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.01it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.22it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.40it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.54it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 16.14it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.21it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.36it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.40it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.37it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.50it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.52it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.46it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.51it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.35it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.10it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.18it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.25it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.17it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.29it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.28it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.34it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.33it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.20it/s]",
  "metrics": {
    "predict_time": 3.362063,
    "total_time": 3.405865
  },
  "output": [
    "https://replicate.delivery/pbxt/S1C3iOdtKNrfGKRflggow2cF7MR9X4TWY6xCxt0i5RQEN07PA/out-0.png"
  ],
  "started_at": "2022-11-01T21:36:01.163256Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/drfj2ccsk5hijcs27xbwwuftwu",
    "cancel": "https://api.replicate.com/v1/predictions/drfj2ccsk5hijcs27xbwwuftwu/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.4 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

ynzx4balnjhnbiwrob33wsf6ti

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: the pyramids of giza
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "the pyramids of giza",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "the pyramids of giza",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "the pyramids of giza",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "the pyramids of giza",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:42:21.811985Z",
  "created_at": "2022-11-01T21:42:18.470413Z",
  "data_removed": false,
  "error": null,
  "id": "ynzx4balnjhnbiwrob33wsf6ti",
  "input": {
    "prompt": "the pyramids of giza",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 45341\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 13.73it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.22it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.77it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 15.88it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.24it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.48it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.64it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.73it/s]\n 35%|███▌      | 18/51 [00:01<00:01, 16.78it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.83it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.89it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.95it/s]\n 51%|█████     | 26/51 [00:01<00:01, 17.01it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 17.04it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 17.06it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 17.09it/s]\n 67%|██████▋   | 34/51 [00:02<00:00, 17.07it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.88it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.87it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.71it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.03it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.30it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.49it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.63it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.71it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.60it/s]",
  "metrics": {
    "predict_time": 3.276683,
    "total_time": 3.341572
  },
  "output": [
    "https://replicate.delivery/pbxt/80H89qPmmjoWNdAIxFL51aHhTxOn8aeDJLMamz3Fn7seS07PA/out-0.png"
  ],
  "started_at": "2022-11-01T21:42:18.535302Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/ynzx4balnjhnbiwrob33wsf6ti",
    "cancel": "https://api.replicate.com/v1/predictions/ynzx4balnjhnbiwrob33wsf6ti/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

jch5led7avbvjk6wvt67jrszb4

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: a sea monster basking in the sun
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "a sea monster basking in the sun",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "a sea monster basking in the sun",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "a sea monster basking in the sun",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "a sea monster basking in the sun",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:43:54.062547Z",
  "created_at": "2022-11-01T21:43:50.655082Z",
  "data_removed": false,
  "error": null,
  "id": "jch5led7avbvjk6wvt67jrszb4",
  "input": {
    "prompt": "a sea monster basking in the sun",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 17530\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.62it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.49it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 16.01it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.27it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.16it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.26it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.32it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.41it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.32it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.44it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.50it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 15.74it/s]\n 51%|█████     | 26/51 [00:01<00:01, 15.75it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.01it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.17it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.08it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.24it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.42it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.35it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.35it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.29it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 15.81it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 15.97it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.11it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.29it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.16it/s]",
  "metrics": {
    "predict_time": 3.36605,
    "total_time": 3.407465
  },
  "output": [
    "https://replicate.delivery/pbxt/XDU9ER6MmjoQP1UxbGXVuwADLSqREsYUZDdWMW4TjeGNK69HA/out-0.png"
  ],
  "started_at": "2022-11-01T21:43:50.696497Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/jch5led7avbvjk6wvt67jrszb4",
    "cancel": "https://api.replicate.com/v1/predictions/jch5led7avbvjk6wvt67jrszb4/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.4 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

pj4scullmnhybkssfokzzu7eka

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.3s

Created

over 2 years ago

Input

prompt: a happy martian alien
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "a happy martian alien",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "a happy martian alien",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "a happy martian alien",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "a happy martian alien",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:46:18.197549Z",
  "created_at": "2022-11-01T21:46:14.878985Z",
  "data_removed": false,
  "error": null,
  "id": "pj4scullmnhybkssfokzzu7eka",
  "input": {
    "prompt": "a happy martian alien",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 10265\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.59it/s]\n  8%|▊         | 4/51 [00:00<00:02, 15.95it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 16.20it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.36it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.32it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.43it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.52it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.58it/s]\n 35%|███▌      | 18/51 [00:01<00:01, 16.61it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.66it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.64it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.63it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.32it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.49it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.64it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.74it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.70it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.69it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.80it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.89it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.53it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.41it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.63it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.78it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.83it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.57it/s]",
  "metrics": {
    "predict_time": 3.28058,
    "total_time": 3.318564
  },
  "output": [
    "https://replicate.delivery/pbxt/vH9Otl1eRDwFZixbLoYvlfTqD69aGaX9oKQfJMeAfPWW1ieeHA/out-0.png"
  ],
  "started_at": "2022-11-01T21:46:14.916969Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/pj4scullmnhybkssfokzzu7eka",
    "cancel": "https://api.replicate.com/v1/predictions/pj4scullmnhybkssfokzzu7eka/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

jzgrlmdgnfg43bvkxh665e4mvq

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: a scene from blade runner
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "a scene from blade runner",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "a scene from blade runner",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "a scene from blade runner",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "a scene from blade runner",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:48:29.360614Z",
  "created_at": "2022-11-01T21:48:26.010682Z",
  "data_removed": false,
  "error": null,
  "id": "jzgrlmdgnfg43bvkxh665e4mvq",
  "input": {
    "prompt": "a scene from blade runner",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 40448\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.50it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.50it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.90it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.24it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.18it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.35it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.47it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.54it/s]\n 35%|███▌      | 18/51 [00:01<00:01, 16.62it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.57it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.22it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 15.65it/s]\n 51%|█████     | 26/51 [00:01<00:01, 15.61it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 15.95it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.22it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.49it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.68it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.81it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.88it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.93it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.78it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.76it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.69it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.84it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.96it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.47it/s]",
  "metrics": {
    "predict_time": 3.309633,
    "total_time": 3.349932
  },
  "output": [
    "https://replicate.delivery/pbxt/wEo43dHNLVLRFVfGcRMaX8M2XYfBGE2gJe1xBB2NYQmaxo3fA/out-0.png"
  ],
  "started_at": "2022-11-01T21:48:26.050981Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/jzgrlmdgnfg43bvkxh665e4mvq",
    "cancel": "https://api.replicate.com/v1/predictions/jzgrlmdgnfg43bvkxh665e4mvq/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

nyq6tazrq5adzfz5vxmkup5iea

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: dinosaurs in jurassic park
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "dinosaurs in jurassic park",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "dinosaurs in jurassic park",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "dinosaurs in jurassic park",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "dinosaurs in jurassic park",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:49:12.391613Z",
  "created_at": "2022-11-01T21:49:09.019936Z",
  "data_removed": false,
  "error": null,
  "id": "nyq6tazrq5adzfz5vxmkup5iea",
  "input": {
    "prompt": "dinosaurs in jurassic park",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 63526\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.93it/s]\n  8%|▊         | 4/51 [00:00<00:02, 15.95it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 16.31it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.46it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.60it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.46it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.49it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.51it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.34it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.50it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.63it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.53it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.53it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.39it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.37it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.41it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.37it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.39it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.41it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.37it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.36it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.27it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.23it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.27it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 15.95it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.32it/s]",
  "metrics": {
    "predict_time": 3.328341,
    "total_time": 3.371677
  },
  "output": [
    "https://replicate.delivery/pbxt/55Iy9FKUpexvICBdRwa3oboT26TbxUXnPJOJIo1UGcBsM69HA/out-0.png"
  ],
  "started_at": "2022-11-01T21:49:09.063272Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/nyq6tazrq5adzfz5vxmkup5iea",
    "cancel": "https://api.replicate.com/v1/predictions/nyq6tazrq5adzfz5vxmkup5iea/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

reiofklsonhwjkgaene7lvpcxa

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: a portrait of a pirate bride and groom
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "a portrait of a pirate bride and groom",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "a portrait of a pirate bride and groom",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "a portrait of a pirate bride and groom",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "a portrait of a pirate bride and groom",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:51:57.179178Z",
  "created_at": "2022-11-01T21:51:53.818904Z",
  "data_removed": false,
  "error": null,
  "id": "reiofklsonhwjkgaene7lvpcxa",
  "input": {
    "prompt": "a portrait of a pirate bride and groom",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 39804\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 13.39it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.18it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.82it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.26it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.54it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.65it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.52it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.24it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.43it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.62it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.70it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.78it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.86it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.86it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.83it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.90it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.87it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.53it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.63it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.74it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.76it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.81it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.87it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.80it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.83it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.60it/s]",
  "metrics": {
    "predict_time": 3.318722,
    "total_time": 3.360274
  },
  "output": [
    "https://replicate.delivery/pbxt/f7XQ2bjVszxOJ66fHUb6wrTvGATPKIO8Z16jaVGabBc9b07PA/out-0.png"
  ],
  "started_at": "2022-11-01T21:51:53.860456Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/reiofklsonhwjkgaene7lvpcxa",
    "cancel": "https://api.replicate.com/v1/predictions/reiofklsonhwjkgaene7lvpcxa/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

d7kkwcjfkzhaznfnitjtslsemu

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: sea turtles on the beach in maui
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "sea turtles on the beach in maui",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "sea turtles on the beach in maui",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "sea turtles on the beach in maui",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "sea turtles on the beach in maui",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:55:38.534757Z",
  "created_at": "2022-11-01T21:55:35.109283Z",
  "data_removed": false,
  "error": null,
  "id": "d7kkwcjfkzhaznfnitjtslsemu",
  "input": {
    "prompt": "sea turtles on the beach in maui",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 9984\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.34it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.31it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.64it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 15.90it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 15.94it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 15.97it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 15.98it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 15.89it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 15.93it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 15.91it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 15.96it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.03it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.11it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.13it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.00it/s]\n 63%|██████▎   | 32/51 [00:02<00:01, 16.12it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.21it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.19it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.24it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.23it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.21it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.26it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.26it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.38it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.45it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.10it/s]",
  "metrics": {
    "predict_time": 3.384878,
    "total_time": 3.425474
  },
  "output": [
    "https://replicate.delivery/pbxt/aJPVT6bLWXbsOR4lNsnfeBGts5iAKR4zdTIuQT897wqafo3fA/out-0.png"
  ],
  "started_at": "2022-11-01T21:55:35.149879Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/d7kkwcjfkzhaznfnitjtslsemu",
    "cancel": "https://api.replicate.com/v1/predictions/d7kkwcjfkzhaznfnitjtslsemu/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.4 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

ljwubvgksve4tdpmvnxdgqbj6e

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

prompt: a house on the berkeley hills
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "a house on the berkeley hills",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "a house on the berkeley hills",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "a house on the berkeley hills",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "a house on the berkeley hills",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:59:08.686811Z",
  "created_at": "2022-11-01T21:59:05.261487Z",
  "data_removed": false,
  "error": null,
  "id": "ljwubvgksve4tdpmvnxdgqbj6e",
  "input": {
    "prompt": "a house on the berkeley hills",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 12530\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.30it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.31it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.59it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.05it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.22it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.15it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.24it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.29it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.24it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 15.86it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.11it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.29it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.16it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.29it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.28it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.42it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.08it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.11it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.31it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.21it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.38it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.47it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.57it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.42it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.35it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.18it/s]",
  "metrics": {
    "predict_time": 3.388422,
    "total_time": 3.425324
  },
  "output": [
    "https://replicate.delivery/pbxt/68bI5Djdj9Z8KBrm6k7Gc0pykccNe7z2MGtVM5QdNfIsi07PA/out-0.png"
  ],
  "started_at": "2022-11-01T21:59:05.298389Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/ljwubvgksve4tdpmvnxdgqbj6e",
    "cancel": "https://api.replicate.com/v1/predictions/ljwubvgksve4tdpmvnxdgqbj6e/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.4 seconds

andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76

Prediction

Model

ID

vhhlj37ghnegha6lhmqxlry554

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.3s

Created

over 2 years ago

Input

prompt: a moose in the swedish woods
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "prompt": "a moose in the swedish woods",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
  {
    input: {
      prompt: "a moose in the swedish woods",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    input={
        "prompt": "a moose in the swedish woods",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76",
    "input": {
      "prompt": "a moose in the swedish woods",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T21:59:46.565619Z",
  "created_at": "2022-11-01T21:59:43.280191Z",
  "data_removed": false,
  "error": null,
  "id": "vhhlj37ghnegha6lhmqxlry554",
  "input": {
    "prompt": "a moose in the swedish woods",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 46371\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.78it/s]\n  8%|▊         | 4/51 [00:00<00:02, 15.90it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.96it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.28it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.53it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.56it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.63it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.71it/s]\n 35%|███▌      | 18/51 [00:01<00:01, 16.77it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.80it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.68it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.79it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.81it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.86it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.91it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.96it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.99it/s]\n 71%|███████   | 36/51 [00:02<00:00, 17.00it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.99it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.74it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.81it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.87it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.94it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 17.01it/s]\n 98%|█████████▊| 50/51 [00:02<00:00, 17.06it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.77it/s]",
  "metrics": {
    "predict_time": 3.247415,
    "total_time": 3.285428
  },
  "output": [
    "https://replicate.delivery/pbxt/OYF7cpW36iLXBhXleuETAcjlkW1fbPfpB0RljuL5mAKlGp3fA/out-0.png"
  ],
  "started_at": "2022-11-01T21:59:43.318204Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/vhhlj37ghnegha6lhmqxlry554",
    "cancel": "https://api.replicate.com/v1/predictions/vhhlj37ghnegha6lhmqxlry554/cancel"
  },
  "version": "792eb5dabf5501925c8d2f8394e06fa26cf17255d0499f4cc11212476b59aa76"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

bbyj4iq3mrcmzpnnfnfybrqmh4

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.6s

Created

over 2 years ago

Input

width: 640
height: 288
prompt: a close up of santa claus flying above snowy finnish woods
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": 288,
  "prompt": "a close up of santa claus flying above snowy finnish woods",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: 288,
      prompt: "a close up of santa claus flying above snowy finnish woods",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": 288,
        "prompt": "a close up of santa claus flying above snowy finnish woods",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": 288,
      "prompt": "a close up of santa claus flying above snowy finnish woods",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T22:05:24.317188Z",
  "created_at": "2022-11-01T22:05:20.723864Z",
  "data_removed": false,
  "error": null,
  "id": "bbyj4iq3mrcmzpnnfnfybrqmh4",
  "input": {
    "width": 640,
    "height": 288,
    "prompt": "a close up of santa claus flying above snowy finnish woods",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 29136\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 13.84it/s]\n  8%|▊         | 4/51 [00:00<00:03, 14.96it/s]\n 12%|█▏        | 6/51 [00:00<00:03, 14.22it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 14.92it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 15.44it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 15.68it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 15.25it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 15.58it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 15.86it/s]\n 39%|███▉      | 20/51 [00:01<00:02, 15.20it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 14.98it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 15.39it/s]\n 51%|█████     | 26/51 [00:01<00:01, 15.64it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 15.26it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 15.61it/s]\n 63%|██████▎   | 32/51 [00:02<00:01, 15.83it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 15.97it/s]\n 71%|███████   | 36/51 [00:02<00:00, 15.61it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 15.55it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 15.85it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.04it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 15.57it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 15.64it/s]\n 94%|█████████▍| 48/51 [00:03<00:00, 15.89it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.11it/s]\n100%|██████████| 51/51 [00:03<00:00, 15.55it/s]",
  "metrics": {
    "predict_time": 3.550837,
    "total_time": 3.593324
  },
  "output": [
    "https://replicate.delivery/pbxt/9YWWVZVlxSI8F1sWMOGcjzPiuBRnnBl9vn9JrrFo1MPJK9eHA/out-0.png"
  ],
  "started_at": "2022-11-01T22:05:20.766351Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/bbyj4iq3mrcmzpnnfnfybrqmh4",
    "cancel": "https://api.replicate.com/v1/predictions/bbyj4iq3mrcmzpnnfnfybrqmh4/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.6 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

w3uetkiuvrfz3fvzkuxpwxwdmu

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.5s

Created

over 2 years ago

Input

width: 640
height: 288
prompt: elvis priestly
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": 288,
  "prompt": "elvis priestly",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: 288,
      prompt: "elvis priestly",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": 288,
        "prompt": "elvis priestly",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": 288,
      "prompt": "elvis priestly",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T22:08:08.032032Z",
  "created_at": "2022-11-01T22:08:04.536471Z",
  "data_removed": false,
  "error": null,
  "id": "w3uetkiuvrfz3fvzkuxpwxwdmu",
  "input": {
    "width": 640,
    "height": 288,
    "prompt": "elvis priestly",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 48393\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 13.98it/s]\n  8%|▊         | 4/51 [00:00<00:03, 14.93it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.58it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 15.77it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 15.59it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 15.84it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.02it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 15.80it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 15.90it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 15.98it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.08it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 15.75it/s]\n 51%|█████     | 26/51 [00:01<00:01, 15.90it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 15.97it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.03it/s]\n 63%|██████▎   | 32/51 [00:02<00:01, 15.81it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 15.85it/s]\n 71%|███████   | 36/51 [00:02<00:00, 15.74it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 15.11it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 15.59it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 15.93it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 15.76it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.06it/s]\n 94%|█████████▍| 48/51 [00:03<00:00, 16.31it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.37it/s]\n100%|██████████| 51/51 [00:03<00:00, 15.84it/s]",
  "metrics": {
    "predict_time": 3.457238,
    "total_time": 3.495561
  },
  "output": [
    "https://replicate.delivery/pbxt/33uJ0ko5uex4QKsBSqft2cU2wUnhXeXpeLrmfAN0GFSEZleeHA/out-0.png"
  ],
  "started_at": "2022-11-01T22:08:04.574794Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/w3uetkiuvrfz3fvzkuxpwxwdmu",
    "cancel": "https://api.replicate.com/v1/predictions/w3uetkiuvrfz3fvzkuxpwxwdmu/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.5 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

nu4pggnq2jhq7eewrpxwexyfky

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.5s

Created

over 2 years ago

Input

width: 640
height: "640"
prompt: la Sagrada Família on a sunny day
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": "640",
  "prompt": "la Sagrada Família on a sunny day",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: "640",
      prompt: "la Sagrada Família on a sunny day",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": "640",
        "prompt": "la Sagrada Família on a sunny day",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": "640",
      "prompt": "la Sagrada Família on a sunny day",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T22:10:23.142794Z",
  "created_at": "2022-11-01T22:10:19.668021Z",
  "data_removed": false,
  "error": null,
  "id": "nu4pggnq2jhq7eewrpxwexyfky",
  "input": {
    "width": 640,
    "height": "640",
    "prompt": "la Sagrada Família on a sunny day",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 15328\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.48it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.54it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.55it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 15.72it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.10it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.39it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.59it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.71it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.36it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.54it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.56it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.43it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.41it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.53it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.60it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.24it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.34it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.43it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 15.66it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 15.97it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 15.83it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.12it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.32it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.48it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.56it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.27it/s]",
  "metrics": {
    "predict_time": 3.437406,
    "total_time": 3.474773
  },
  "output": [
    "https://replicate.delivery/pbxt/1bvJE0b4mtrVIBq0wgBvfPwYTf3IafSmeeWAAt7lBVO6pleeHA/out-0.png"
  ],
  "started_at": "2022-11-01T22:10:19.705388Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/nu4pggnq2jhq7eewrpxwexyfky",
    "cancel": "https://api.replicate.com/v1/predictions/nu4pggnq2jhq7eewrpxwexyfky/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.4 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

olb5tkunozaejfdda6ouwqqa2a

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.6s

Created

over 2 years ago

Input

width: 640
height: 288
prompt: a lighthouse by the sea
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": 288,
  "prompt": "a lighthouse by the sea",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: 288,
      prompt: "a lighthouse by the sea",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": 288,
        "prompt": "a lighthouse by the sea",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": 288,
      "prompt": "a lighthouse by the sea",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T22:29:26.976958Z",
  "created_at": "2022-11-01T22:29:23.354927Z",
  "data_removed": false,
  "error": null,
  "id": "olb5tkunozaejfdda6ouwqqa2a",
  "input": {
    "width": 640,
    "height": 288,
    "prompt": "a lighthouse by the sea",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 19488\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 12.99it/s]\n  8%|▊         | 4/51 [00:00<00:03, 13.98it/s]\n 12%|█▏        | 6/51 [00:00<00:03, 14.22it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 14.70it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 14.96it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 14.85it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 14.78it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 15.02it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 15.21it/s]\n 39%|███▉      | 20/51 [00:01<00:02, 15.36it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 15.25it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 15.46it/s]\n 51%|█████     | 26/51 [00:01<00:01, 15.57it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 15.35it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 15.49it/s]\n 63%|██████▎   | 32/51 [00:02<00:01, 15.64it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 15.75it/s]\n 71%|███████   | 36/51 [00:02<00:00, 15.81it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 15.63it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 15.44it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 15.32it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 15.46it/s]\n 90%|█████████ | 46/51 [00:03<00:00, 15.60it/s]\n 94%|█████████▍| 48/51 [00:03<00:00, 15.64it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 15.66it/s]\n100%|██████████| 51/51 [00:03<00:00, 15.32it/s]",
  "metrics": {
    "predict_time": 3.585673,
    "total_time": 3.622031
  },
  "output": [
    "https://replicate.delivery/pbxt/0MFGDub73kZwK5ktLhSpXntQnSCmy9T2zQOEAsjcTZsxP9eHA/out-0.png"
  ],
  "started_at": "2022-11-01T22:29:23.391285Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/olb5tkunozaejfdda6ouwqqa2a",
    "cancel": "https://api.replicate.com/v1/predictions/olb5tkunozaejfdda6ouwqqa2a/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.6 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

g2d3w6yk6fhqfafvd4uyyie7uu

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

width: 640
height: 288
prompt: off road trucking
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": 288,
  "prompt": "off road trucking",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: 288,
      prompt: "off road trucking",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": 288,
        "prompt": "off road trucking",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": 288,
      "prompt": "off road trucking",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T23:10:18.355927Z",
  "created_at": "2022-11-01T23:10:14.995336Z",
  "data_removed": false,
  "error": null,
  "id": "g2d3w6yk6fhqfafvd4uyyie7uu",
  "input": {
    "width": 640,
    "height": 288,
    "prompt": "off road trucking",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 5679\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 13.54it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.26it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 15.88it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.18it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.23it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.24it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.16it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.37it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.47it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.50it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.46it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.59it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.71it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.77it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.76it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.80it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.83it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.77it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.70it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.58it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.33it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.50it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.43it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.53it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.60it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.45it/s]",
  "metrics": {
    "predict_time": 3.321897,
    "total_time": 3.360591
  },
  "output": [
    "https://replicate.delivery/pbxt/y4n9aC64jdYJO5Vf3Q15C9T8wGMBXtaedY3omP6MlQJal17PA/out-0.png"
  ],
  "started_at": "2022-11-01T23:10:15.034030Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/g2d3w6yk6fhqfafvd4uyyie7uu",
    "cancel": "https://api.replicate.com/v1/predictions/g2d3w6yk6fhqfafvd4uyyie7uu/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

kwtlzniswfaa5g35xzgstijkfu

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.4s

Created

over 2 years ago

Input

width: 640
height: 288
prompt: an elephant
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": 288,
  "prompt": "an elephant",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: 288,
      prompt: "an elephant",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": 288,
        "prompt": "an elephant",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": 288,
      "prompt": "an elephant",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T23:28:54.549400Z",
  "created_at": "2022-11-01T23:28:51.178131Z",
  "data_removed": false,
  "error": null,
  "id": "kwtlzniswfaa5g35xzgstijkfu",
  "input": {
    "width": 640,
    "height": 288,
    "prompt": "an elephant",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 64265\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 14.83it/s]\n  8%|▊         | 4/51 [00:00<00:02, 16.02it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 16.45it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.59it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 15.85it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 15.89it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.24it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.24it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.48it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.61it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.67it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.74it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.80it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.88it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 16.93it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 16.97it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.69it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.78it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.86it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.92it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.65it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.77it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.85it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.23it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.16it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.45it/s]",
  "metrics": {
    "predict_time": 3.335566,
    "total_time": 3.371269
  },
  "output": [
    "https://replicate.delivery/pbxt/3DbahbR1LEqRJhMST0r6o5WbvuSO9E06IOio6UXptJktd9eHA/out-0.png"
  ],
  "started_at": "2022-11-01T23:28:51.213834Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/kwtlzniswfaa5g35xzgstijkfu",
    "cancel": "https://api.replicate.com/v1/predictions/kwtlzniswfaa5g35xzgstijkfu/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.3 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

lrrlqak6rvbl5ozt4hpf7xq2oq

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.7s

Created

over 2 years ago

Input

width: 640
height: "640"
prompt: tom cruise as a pirate
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": "640",
  "prompt": "tom cruise as a pirate",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: "640",
      prompt: "tom cruise as a pirate",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": "640",
        "prompt": "tom cruise as a pirate",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": "640",
      "prompt": "tom cruise as a pirate",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T23:32:34.286546Z",
  "created_at": "2022-11-01T23:32:30.625999Z",
  "data_removed": false,
  "error": null,
  "id": "lrrlqak6rvbl5ozt4hpf7xq2oq",
  "input": {
    "width": 640,
    "height": "640",
    "prompt": "tom cruise as a pirate",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 31764\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:04, 12.19it/s]\n  8%|▊         | 4/51 [00:00<00:03, 13.09it/s]\n 12%|█▏        | 6/51 [00:00<00:03, 13.42it/s]\n 16%|█▌        | 8/51 [00:00<00:03, 13.60it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 14.35it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 15.12it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 15.64it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 15.35it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 14.87it/s]\n 39%|███▉      | 20/51 [00:01<00:02, 14.56it/s]\n 43%|████▎     | 22/51 [00:01<00:02, 14.36it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 14.34it/s]\n 51%|█████     | 26/51 [00:01<00:01, 15.05it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 15.54it/s]\n 59%|█████▉    | 30/51 [00:02<00:01, 15.21it/s]\n 63%|██████▎   | 32/51 [00:02<00:01, 15.20it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 15.70it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.09it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 16.36it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.55it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.71it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.83it/s]\n 90%|█████████ | 46/51 [00:03<00:00, 16.49it/s]\n 94%|█████████▍| 48/51 [00:03<00:00, 16.26it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.42it/s]\n100%|██████████| 51/51 [00:03<00:00, 15.35it/s]",
  "metrics": {
    "predict_time": 3.62243,
    "total_time": 3.660547
  },
  "output": [
    "https://replicate.delivery/pbxt/4i4TjQo71QbgAVFCeSYdhfYgicAraGj24D3fX4OC43Hk0r3fA/out-0.png"
  ],
  "started_at": "2022-11-01T23:32:30.664116Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/lrrlqak6rvbl5ozt4hpf7xq2oq",
    "cancel": "https://api.replicate.com/v1/predictions/lrrlqak6rvbl5ozt4hpf7xq2oq/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.6 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

xj2af7ztarc7hnnqrdz4lexedm

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

3.6s

Created

over 2 years ago

Input

width: 640
height: "640"
prompt: anna wintour as a pirate
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": "640",
  "prompt": "anna wintour as a pirate",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: "640",
      prompt: "anna wintour as a pirate",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": "640",
        "prompt": "anna wintour as a pirate",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": "640",
      "prompt": "anna wintour as a pirate",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T23:34:22.253222Z",
  "created_at": "2022-11-01T23:34:18.672178Z",
  "data_removed": false,
  "error": null,
  "id": "xj2af7ztarc7hnnqrdz4lexedm",
  "input": {
    "width": 640,
    "height": "640",
    "prompt": "anna wintour as a pirate",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 10159\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 12.30it/s]\n  8%|▊         | 4/51 [00:00<00:03, 13.69it/s]\n 12%|█▏        | 6/51 [00:00<00:03, 13.70it/s]\n 16%|█▌        | 8/51 [00:00<00:03, 13.60it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 13.84it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 14.77it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 15.33it/s]\n 31%|███▏      | 16/51 [00:01<00:02, 15.72it/s]\n 35%|███▌      | 18/51 [00:01<00:02, 16.02it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.35it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.58it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.73it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.86it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 16.95it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 17.01it/s]\n 63%|██████▎   | 32/51 [00:02<00:01, 16.55it/s]\n 67%|██████▋   | 34/51 [00:02<00:01, 16.61it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.09it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 15.31it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 14.92it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 15.52it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 15.84it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.23it/s]\n 94%|█████████▍| 48/51 [00:03<00:00, 16.52it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.63it/s]\n100%|██████████| 51/51 [00:03<00:00, 15.82it/s]",
  "metrics": {
    "predict_time": 3.513804,
    "total_time": 3.581044
  },
  "output": [
    "https://replicate.delivery/pbxt/fKrVSppVibyzXSB69yTGUPwkQ43cx8jfRp3lQHHKfUL93r3fA/out-0.png"
  ],
  "started_at": "2022-11-01T23:34:18.739418Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/xj2af7ztarc7hnnqrdz4lexedm",
    "cancel": "https://api.replicate.com/v1/predictions/xj2af7ztarc7hnnqrdz4lexedm/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.5 seconds

andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9

Prediction

Model

ID

3o2lzm4vxbhupmggkjxxqugaxe

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

8.8s

Created

over 2 years ago by @andreasjansson

Input

width: 640
height: "640"
prompt: einstein as a pirate
num_outputs: 1
guidance_scale: 7.5
num_inference_steps: 50

{
  "width": 640,
  "height": "640",
  "prompt": "einstein as a pirate",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
  {
    input: {
      width: 640,
      height: "640",
      prompt: "einstein as a pirate",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

Run andreasjansson/monkey-island-sd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    input={
        "width": 640,
        "height": "640",
        "prompt": "einstein as a pirate",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Run andreasjansson/monkey-island-sd 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": "andreasjansson/monkey-island-sd:d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9",
    "input": {
      "width": 640,
      "height": "640",
      "prompt": "einstein as a pirate",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2022-11-01T23:38:23.962328Z",
  "created_at": "2022-11-01T23:38:15.173521Z",
  "data_removed": false,
  "error": null,
  "id": "3o2lzm4vxbhupmggkjxxqugaxe",
  "input": {
    "width": 640,
    "height": "640",
    "prompt": "einstein as a pirate",
    "num_outputs": 1,
    "guidance_scale": 7.5,
    "num_inference_steps": 50
  },
  "logs": "Using seed: 64041\n\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:03, 13.62it/s]\n  8%|▊         | 4/51 [00:00<00:03, 15.36it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 16.04it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 16.32it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 16.39it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 16.58it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.74it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.77it/s]\n 35%|███▌      | 18/51 [00:01<00:01, 16.87it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.74it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 16.81it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 16.89it/s]\n 51%|█████     | 26/51 [00:01<00:01, 16.93it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 17.01it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 17.05it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 17.09it/s]\n 67%|██████▋   | 34/51 [00:02<00:00, 17.07it/s]\n 71%|███████   | 36/51 [00:02<00:00, 16.80it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 15.90it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 16.24it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 16.36it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 16.28it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 16.31it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 16.49it/s]\n 98%|█████████▊| 50/51 [00:03<00:00, 16.18it/s]\n100%|██████████| 51/51 [00:03<00:00, 16.51it/s]",
  "metrics": {
    "predict_time": 3.371568,
    "total_time": 8.788807
  },
  "output": [
    "https://replicate.delivery/pbxt/gHOQMNbVxZL2Edx5JU77AbJiBcNGDUunAazD9Iteavx3f17PA/out-0.png"
  ],
  "started_at": "2022-11-01T23:38:20.590760Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/3o2lzm4vxbhupmggkjxxqugaxe",
    "cancel": "https://api.replicate.com/v1/predictions/3o2lzm4vxbhupmggkjxxqugaxe/cancel"
  },
  "version": "d4c14b78d93ea8a6537bf73a8c83af8cdb0c31795ff7ebaa91ff9a041b7077f9"
}

Generated in

3.4 seconds