Prediction

Model

andreasjansson/monkey-island-rdm:2c737891

kvza5yr4nrbkzk6fkdtyhpm3qi

Status

Succeeded

Source

Web

Hardware

–

Total duration

8.9s

Created

over 3 years ago

Webhook

–

Input

prompt: An enormous monster alien on a distant planet
scale: 5
num_database_results: 10
steps: 100
seed: -1

{
  "num_database_results": "10",
  "prompt": "An enormous monster alien on a distant planet",
  "scale": 5,
  "seed": -1,
  "steps": 100
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Poc**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run andreasjansson/monkey-island-rdm 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-rdm:2c737891c668aa2a759ea6db63b35d3a4f569a803dbad2446c872475c4fb6c63",
  {
    input: {
      num_database_results: "10",
      prompt: "An enormous monster alien on a distant planet",
      scale: 5,
      seed: -1,
      steps: 100
    }
  }
);

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

// To write the file to disk:
fs.writeFile("my-image.png", output);

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

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Poc**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

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

output = replicate.run(
    "andreasjansson/monkey-island-rdm:2c737891c668aa2a759ea6db63b35d3a4f569a803dbad2446c872475c4fb6c63",
    input={
        "num_database_results": "10",
        "prompt": "An enormous monster alien on a distant planet",
        "scale": 5,
        "seed": -1,
        "steps": 100
    }
)

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

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

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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Poc**********************************

This is your API token. Keep it to yourself.

Run andreasjansson/monkey-island-rdm 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-rdm:2c737891c668aa2a759ea6db63b35d3a4f569a803dbad2446c872475c4fb6c63",
    "input": {
      "num_database_results": "10",
      "prompt": "An enormous monster alien on a distant planet",
      "scale": 5,
      "seed": -1,
      "steps": 100
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "kvza5yr4nrbkzk6fkdtyhpm3qi",
  "model": "andreasjansson/monkey-island-rdm",
  "version": "2c737891c668aa2a759ea6db63b35d3a4f569a803dbad2446c872475c4fb6c63",
  "input": {
    "num_database_results": "10",
    "prompt": "An enormous monster alien on a distant planet",
    "scale": 5,
    "seed": -1,
    "steps": 100
  },
  "logs": "Using random seed 3029702370\nSeed: -1\nCLIP Text Embed: torch.Size([1, 1, 768])\nData shape for PLMS sampling is (1, 16, 48, 48)\nRunning PLMS Sampling with 100 timesteps\n\nPLMS Sampler:   0%|          | 0/100 [00:00<?, ?it/s]\nPLMS Sampler:   1%|          | 1/100 [00:00<00:16,  6.10it/s]\nPLMS Sampler:   3%|▎         | 3/100 [00:00<00:09, 10.21it/s]\nPLMS Sampler:   5%|▌         | 5/100 [00:00<00:08, 11.81it/s]\nPLMS Sampler:   7%|▋         | 7/100 [00:00<00:07, 12.60it/s]\nPLMS Sampler:   9%|▉         | 9/100 [00:00<00:06, 13.04it/s]\nPLMS Sampler:  11%|█         | 11/100 [00:00<00:06, 13.33it/s]\nPLMS Sampler:  13%|█▎        | 13/100 [00:01<00:06, 13.13it/s]\nPLMS Sampler:  15%|█▌        | 15/100 [00:01<00:06, 13.28it/s]\nPLMS Sampler:  17%|█▋        | 17/100 [00:01<00:06, 13.42it/s]\nPLMS Sampler:  19%|█▉        | 19/100 [00:01<00:05, 13.57it/s]\nPLMS Sampler:  21%|██        | 21/100 [00:01<00:05, 13.63it/s]\nPLMS Sampler:  23%|██▎       | 23/100 [00:01<00:05, 13.72it/s]\nPLMS Sampler:  25%|██▌       | 25/100 [00:01<00:05, 13.52it/s]\nPLMS Sampler:  27%|██▋       | 27/100 [00:02<00:05, 13.49it/s]\nPLMS Sampler:  29%|██▉       | 29/100 [00:02<00:05, 13.61it/s]\nPLMS Sampler:  31%|███       | 31/100 [00:02<00:05, 13.67it/s]\nPLMS Sampler:  33%|███▎      | 33/100 [00:02<00:04, 13.73it/s]\nPLMS Sampler:  35%|███▌      | 35/100 [00:02<00:04, 13.57it/s]\nPLMS Sampler:  37%|███▋      | 37/100 [00:02<00:04, 13.58it/s]\nPLMS Sampler:  39%|███▉      | 39/100 [00:02<00:04, 13.31it/s]\nPLMS Sampler:  41%|████      | 41/100 [00:03<00:04, 13.39it/s]\nPLMS Sampler:  43%|████▎     | 43/100 [00:03<00:04, 13.49it/s]\nPLMS Sampler:  45%|████▌     | 45/100 [00:03<00:04, 13.62it/s]\nPLMS Sampler:  47%|████▋     | 47/100 [00:03<00:03, 13.57it/s]\nPLMS Sampler:  49%|████▉     | 49/100 [00:03<00:03, 13.70it/s]\nPLMS Sampler:  51%|█████     | 51/100 [00:03<00:03, 13.79it/s]\nPLMS Sampler:  53%|█████▎    | 53/100 [00:03<00:03, 13.83it/s]\nPLMS Sampler:  55%|█████▌    | 55/100 [00:04<00:03, 13.85it/s]\nPLMS Sampler:  57%|█████▋    | 57/100 [00:04<00:03, 13.84it/s]\nPLMS Sampler:  59%|█████▉    | 59/100 [00:04<00:02, 13.87it/s]\nPLMS Sampler:  61%|██████    | 61/100 [00:04<00:02, 13.91it/s]\nPLMS Sampler:  63%|██████▎   | 63/100 [00:04<00:02, 13.93it/s]\nPLMS Sampler:  65%|██████▌   | 65/100 [00:04<00:02, 13.92it/s]\nPLMS Sampler:  67%|██████▋   | 67/100 [00:04<00:02, 13.89it/s]\nPLMS Sampler:  69%|██████▉   | 69/100 [00:05<00:02, 13.88it/s]\nPLMS Sampler:  71%|███████   | 71/100 [00:05<00:02, 13.87it/s]\nPLMS Sampler:  73%|███████▎  | 73/100 [00:05<00:02, 13.46it/s]\nPLMS Sampler:  75%|███████▌  | 75/100 [00:05<00:01, 13.61it/s]\nPLMS Sampler:  77%|███████▋  | 77/100 [00:05<00:01, 13.26it/s]\nPLMS Sampler:  79%|███████▉  | 79/100 [00:05<00:01, 13.07it/s]\nPLMS Sampler:  81%|████████  | 81/100 [00:06<00:01, 13.29it/s]\nPLMS Sampler:  83%|████████▎ | 83/100 [00:06<00:01, 13.47it/s]\nPLMS Sampler:  85%|████████▌ | 85/100 [00:06<00:01, 13.61it/s]\nPLMS Sampler:  87%|████████▋ | 87/100 [00:06<00:00, 13.69it/s]\nPLMS Sampler:  89%|████████▉ | 89/100 [00:06<00:00, 13.76it/s]\nPLMS Sampler:  91%|█████████ | 91/100 [00:06<00:00, 13.73it/s]\nPLMS Sampler:  93%|█████████▎| 93/100 [00:06<00:00, 13.74it/s]\nPLMS Sampler:  95%|█████████▌| 95/100 [00:07<00:00, 13.75it/s]\nPLMS Sampler:  97%|█████████▋| 97/100 [00:07<00:00, 13.77it/s]\nPLMS Sampler:  99%|█████████▉| 99/100 [00:07<00:00, 13.80it/s]\nPLMS Sampler: 100%|██████████| 100/100 [00:07<00:00, 13.49it/s]",
  "output": "https://replicate.delivery/mgxm/cd6f1508-6e00-42d6-b10d-ef8233138559/out.png",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2022-08-19T16:52:57.152417Z",
  "started_at": "2022-08-19T16:52:57.348776Z",
  "completed_at": "2022-08-19T16:53:06.069317Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/kvza5yr4nrbkzk6fkdtyhpm3qi/cancel",
    "get": "https://api.replicate.com/v1/predictions/kvza5yr4nrbkzk6fkdtyhpm3qi"
  },
  "metrics": {
    "predict_time": 8.720541,
    "total_time": 8.9169
  }
}

Generated in

8.7 seconds

Tweak it Report

Using random seed 3029702370 Seed: -1 CLIP Text Embed: torch.Size([1, 1, 768]) Data shape for PLMS sampling is (1, 16, 48, 48) Running PLMS Sampling with 100 timesteps PLMS Sampler: 0%| | 0/100 [00:00<?, ?it/s] PLMS Sampler: 1%| | 1/100 [00:00<00:16, 6.10it/s] PLMS Sampler: 3%|▎ | 3/100 [00:00<00:09, 10.21it/s] PLMS Sampler: 5%|▌ | 5/100 [00:00<00:08, 11.81it/s] PLMS Sampler: 7%|▋ | 7/100 [00:00<00:07, 12.60it/s] PLMS Sampler: 9%|▉ | 9/100 [00:00<00:06, 13.04it/s] PLMS Sampler: 11%|█ | 11/100 [00:00<00:06, 13.33it/s] PLMS Sampler: 13%|█▎ | 13/100 [00:01<00:06, 13.13it/s] PLMS Sampler: 15%|█▌ | 15/100 [00:01<00:06, 13.28it/s] PLMS Sampler: 17%|█▋ | 17/100 [00:01<00:06, 13.42it/s] PLMS Sampler: 19%|█▉ | 19/100 [00:01<00:05, 13.57it/s] PLMS Sampler: 21%|██ | 21/100 [00:01<00:05, 13.63it/s] PLMS Sampler: 23%|██▎ | 23/100 [00:01<00:05, 13.72it/s] PLMS Sampler: 25%|██▌ | 25/100 [00:01<00:05, 13.52it/s] PLMS Sampler: 27%|██▋ | 27/100 [00:02<00:05, 13.49it/s] PLMS Sampler: 29%|██▉ | 29/100 [00:02<00:05, 13.61it/s] PLMS Sampler: 31%|███ | 31/100 [00:02<00:05, 13.67it/s] PLMS Sampler: 33%|███▎ | 33/100 [00:02<00:04, 13.73it/s] PLMS Sampler: 35%|███▌ | 35/100 [00:02<00:04, 13.57it/s] PLMS Sampler: 37%|███▋ | 37/100 [00:02<00:04, 13.58it/s] PLMS Sampler: 39%|███▉ | 39/100 [00:02<00:04, 13.31it/s] PLMS Sampler: 41%|████ | 41/100 [00:03<00:04, 13.39it/s] PLMS Sampler: 43%|████▎ | 43/100 [00:03<00:04, 13.49it/s] PLMS Sampler: 45%|████▌ | 45/100 [00:03<00:04, 13.62it/s] PLMS Sampler: 47%|████▋ | 47/100 [00:03<00:03, 13.57it/s] PLMS Sampler: 49%|████▉ | 49/100 [00:03<00:03, 13.70it/s] PLMS Sampler: 51%|█████ | 51/100 [00:03<00:03, 13.79it/s] PLMS Sampler: 53%|█████▎ | 53/100 [00:03<00:03, 13.83it/s] PLMS Sampler: 55%|█████▌ | 55/100 [00:04<00:03, 13.85it/s] PLMS Sampler: 57%|█████▋ | 57/100 [00:04<00:03, 13.84it/s] PLMS Sampler: 59%|█████▉ | 59/100 [00:04<00:02, 13.87it/s] PLMS Sampler: 61%|██████ | 61/100 [00:04<00:02, 13.91it/s] PLMS Sampler: 63%|██████▎ | 63/100 [00:04<00:02, 13.93it/s] PLMS Sampler: 65%|██████▌ | 65/100 [00:04<00:02, 13.92it/s] PLMS Sampler: 67%|██████▋ | 67/100 [00:04<00:02, 13.89it/s] PLMS Sampler: 69%|██████▉ | 69/100 [00:05<00:02, 13.88it/s] PLMS Sampler: 71%|███████ | 71/100 [00:05<00:02, 13.87it/s] PLMS Sampler: 73%|███████▎ | 73/100 [00:05<00:02, 13.46it/s] PLMS Sampler: 75%|███████▌ | 75/100 [00:05<00:01, 13.61it/s] PLMS Sampler: 77%|███████▋ | 77/100 [00:05<00:01, 13.26it/s] PLMS Sampler: 79%|███████▉ | 79/100 [00:05<00:01, 13.07it/s] PLMS Sampler: 81%|████████ | 81/100 [00:06<00:01, 13.29it/s] PLMS Sampler: 83%|████████▎ | 83/100 [00:06<00:01, 13.47it/s] PLMS Sampler: 85%|████████▌ | 85/100 [00:06<00:01, 13.61it/s] PLMS Sampler: 87%|████████▋ | 87/100 [00:06<00:00, 13.69it/s] PLMS Sampler: 89%|████████▉ | 89/100 [00:06<00:00, 13.76it/s] PLMS Sampler: 91%|█████████ | 91/100 [00:06<00:00, 13.73it/s] PLMS Sampler: 93%|█████████▎| 93/100 [00:06<00:00, 13.74it/s] PLMS Sampler: 95%|█████████▌| 95/100 [00:07<00:00, 13.75it/s] PLMS Sampler: 97%|█████████▋| 97/100 [00:07<00:00, 13.77it/s] PLMS Sampler: 99%|█████████▉| 99/100 [00:07<00:00, 13.80it/s] PLMS Sampler: 100%|██████████| 100/100 [00:07<00:00, 13.49it/s]