Prediction

ID

p2zs35jbgkhq3z3467wejlmt4y

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

5.2s

Created

almost 2 years ago

Input

width: 1024
height: 1024
prompt: Astronaut in a jungle, cold color palette, muted colors, detailed, 8k
negative_prompt: low resolution, low detail, bad quality, blurry
prior_guidance_scale: 4
num_images_per_prompt: 2
decoder_guidance_scale: 0
prior_num_inference_steps: 30
decoder_num_inference_steps: 12

{
  "width": 1024,
  "height": 1024,
  "prompt": "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
  "negative_prompt": "low resolution, low detail, bad quality, blurry",
  "prior_guidance_scale": 4,
  "num_images_per_prompt": 2,
  "decoder_guidance_scale": 0,
  "prior_num_inference_steps": 30,
  "decoder_num_inference_steps": 12
}

npm install replicate

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 cjwbw/wuerstchen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
      negative_prompt: "low resolution, low detail, bad quality, blurry",
      prior_guidance_scale: 4,
      num_images_per_prompt: 2,
      decoder_guidance_scale: 0,
      prior_num_inference_steps: 30,
      decoder_num_inference_steps: 12
    }
  }
);

// 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 cjwbw/wuerstchen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
        "negative_prompt": "low resolution, low detail, bad quality, blurry",
        "prior_guidance_scale": 4,
        "num_images_per_prompt": 2,
        "decoder_guidance_scale": 0,
        "prior_num_inference_steps": 30,
        "decoder_num_inference_steps": 12
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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

Run cjwbw/wuerstchen 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": "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
      "negative_prompt": "low resolution, low detail, bad quality, blurry",
      "prior_guidance_scale": 4,
      "num_images_per_prompt": 2,
      "decoder_guidance_scale": 0,
      "prior_num_inference_steps": 30,
      "decoder_num_inference_steps": 12
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-09-16T01:59:10.907950Z",
  "created_at": "2023-09-16T01:59:05.677833Z",
  "data_removed": false,
  "error": null,
  "id": "p2zs35jbgkhq3z3467wejlmt4y",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
    "negative_prompt": "low resolution, low detail, bad quality, blurry",
    "prior_guidance_scale": 4,
    "num_images_per_prompt": 2,
    "decoder_guidance_scale": 0,
    "prior_num_inference_steps": 30,
    "decoder_num_inference_steps": 12
  },
  "logs": "Using seed: 27739\n  0%|          | 0/29 [00:00<?, ?it/s]\n  7%|▋         | 2/29 [00:00<00:01, 15.35it/s]\n 14%|█▍        | 4/29 [00:00<00:01, 17.11it/s]\n 21%|██        | 6/29 [00:00<00:01, 17.90it/s]\n 28%|██▊       | 8/29 [00:00<00:01, 18.53it/s]\n 34%|███▍      | 10/29 [00:00<00:01, 18.90it/s]\n 41%|████▏     | 12/29 [00:00<00:00, 19.12it/s]\n 48%|████▊     | 14/29 [00:00<00:00, 19.05it/s]\n 55%|█████▌    | 16/29 [00:00<00:00, 19.30it/s]\n 62%|██████▏   | 18/29 [00:00<00:00, 19.32it/s]\n 69%|██████▉   | 20/29 [00:01<00:00, 19.48it/s]\n 76%|███████▌  | 22/29 [00:01<00:00, 19.42it/s]\n 83%|████████▎ | 24/29 [00:01<00:00, 19.42it/s]\n 90%|████████▉ | 26/29 [00:01<00:00, 19.45it/s]\n 97%|█████████▋| 28/29 [00:01<00:00, 19.54it/s]\n100%|██████████| 29/29 [00:01<00:00, 19.06it/s]\n  0%|          | 0/12 [00:00<?, ?it/s]\n  8%|▊         | 1/12 [00:00<00:01,  7.49it/s]\n 25%|██▌       | 3/12 [00:00<00:00,  9.98it/s]\n 42%|████▏     | 5/12 [00:00<00:00, 10.71it/s]\n 58%|█████▊    | 7/12 [00:00<00:00, 10.94it/s]\n 75%|███████▌  | 9/12 [00:00<00:00, 11.01it/s]\n 92%|█████████▏| 11/12 [00:01<00:00, 11.14it/s]\n100%|██████████| 12/12 [00:01<00:00, 10.85it/s]",
  "metrics": {
    "predict_time": 5.267431,
    "total_time": 5.230117
  },
  "output": [
    "https://replicate.delivery/pbxt/KBNvWH9jPd59GlkGr3eBIrGK68JeM9KZW9LfTA89TKe2eeKZE/out-0.png",
    "https://replicate.delivery/pbxt/TpjNTOeoAh0JNihwGUuG4dLYgLhyZcpzIH2LA7Y5cRA37VyIA/out-1.png"
  ],
  "started_at": "2023-09-16T01:59:05.640519Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/p2zs35jbgkhq3z3467wejlmt4y",
    "cancel": "https://api.replicate.com/v1/predictions/p2zs35jbgkhq3z3467wejlmt4y/cancel"
  },
  "version": "6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039"
}

Generated in

5.3 seconds

cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039

Prediction

Model

ID

ppsuuwbbi7ali2hb3ovd3xqj6e

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

5.4s

Created

almost 2 years ago

Input

width: 1024
height: 1024
prompt: A wolf in a detective suit solving a mystery
negative_prompt
prior_guidance_scale: 4
num_images_per_prompt: 2
decoder_guidance_scale: 0
prior_num_inference_steps: 30
decoder_num_inference_steps: 12

{
  "width": 1024,
  "height": 1024,
  "prompt": "A wolf in a detective suit solving a mystery",
  "negative_prompt": "",
  "prior_guidance_scale": 4,
  "num_images_per_prompt": 2,
  "decoder_guidance_scale": 0,
  "prior_num_inference_steps": 30,
  "decoder_num_inference_steps": 12
}

npm install replicate

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 cjwbw/wuerstchen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "A wolf in a detective suit solving a mystery",
      negative_prompt: "",
      prior_guidance_scale: 4,
      num_images_per_prompt: 2,
      decoder_guidance_scale: 0,
      prior_num_inference_steps: 30,
      decoder_num_inference_steps: 12
    }
  }
);

// 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 cjwbw/wuerstchen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "A wolf in a detective suit solving a mystery",
        "negative_prompt": "",
        "prior_guidance_scale": 4,
        "num_images_per_prompt": 2,
        "decoder_guidance_scale": 0,
        "prior_num_inference_steps": 30,
        "decoder_num_inference_steps": 12
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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

Run cjwbw/wuerstchen 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": "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "A wolf in a detective suit solving a mystery",
      "negative_prompt": "",
      "prior_guidance_scale": 4,
      "num_images_per_prompt": 2,
      "decoder_guidance_scale": 0,
      "prior_num_inference_steps": 30,
      "decoder_num_inference_steps": 12
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-09-16T02:01:10.458859Z",
  "created_at": "2023-09-16T02:01:05.041319Z",
  "data_removed": false,
  "error": null,
  "id": "ppsuuwbbi7ali2hb3ovd3xqj6e",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "A wolf in a detective suit solving a mystery",
    "negative_prompt": "",
    "prior_guidance_scale": 4,
    "num_images_per_prompt": 2,
    "decoder_guidance_scale": 0,
    "prior_num_inference_steps": 30,
    "decoder_num_inference_steps": 12
  },
  "logs": "Using seed: 21169\n  0%|          | 0/29 [00:00<?, ?it/s]\n  7%|▋         | 2/29 [00:00<00:01, 17.64it/s]\n 14%|█▍        | 4/29 [00:00<00:01, 18.72it/s]\n 21%|██        | 6/29 [00:00<00:01, 18.88it/s]\n 28%|██▊       | 8/29 [00:00<00:01, 18.83it/s]\n 34%|███▍      | 10/29 [00:00<00:00, 19.11it/s]\n 41%|████▏     | 12/29 [00:00<00:00, 19.31it/s]\n 48%|████▊     | 14/29 [00:00<00:00, 19.32it/s]\n 55%|█████▌    | 16/29 [00:00<00:00, 19.46it/s]\n 62%|██████▏   | 18/29 [00:00<00:00, 19.44it/s]\n 69%|██████▉   | 20/29 [00:01<00:00, 19.52it/s]\n 76%|███████▌  | 22/29 [00:01<00:00, 19.65it/s]\n 83%|████████▎ | 24/29 [00:01<00:00, 19.71it/s]\n 90%|████████▉ | 26/29 [00:01<00:00, 19.48it/s]\n 97%|█████████▋| 28/29 [00:01<00:00, 19.54it/s]\n100%|██████████| 29/29 [00:01<00:00, 19.35it/s]\n  0%|          | 0/12 [00:00<?, ?it/s]\n 17%|█▋        | 2/12 [00:00<00:00, 11.08it/s]\n 33%|███▎      | 4/12 [00:00<00:00, 11.32it/s]\n 50%|█████     | 6/12 [00:00<00:00, 11.38it/s]\n 67%|██████▋   | 8/12 [00:00<00:00, 11.43it/s]\n 83%|████████▎ | 10/12 [00:00<00:00, 11.39it/s]\n100%|██████████| 12/12 [00:01<00:00, 11.37it/s]\n100%|██████████| 12/12 [00:01<00:00, 11.36it/s]",
  "metrics": {
    "predict_time": 5.454779,
    "total_time": 5.41754
  },
  "output": [
    "https://replicate.delivery/pbxt/aUmDitb07rL0Ddzz9eALw81ZaUT5YOjrEexIee7WLf8gMfKZE/out-0.png",
    "https://replicate.delivery/pbxt/zNGGDLVw4EoxP99tmFF9wKdYVOe5py3jXeFOKdeG0D8KzXJjA/out-1.png"
  ],
  "started_at": "2023-09-16T02:01:05.004080Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/ppsuuwbbi7ali2hb3ovd3xqj6e",
    "cancel": "https://api.replicate.com/v1/predictions/ppsuuwbbi7ali2hb3ovd3xqj6e/cancel"
  },
  "version": "6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039"
}

Generated in

5.5 seconds

cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039

Prediction

Model

ID

lsu7r7bbpgptzr5fhoq5io4pw4

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

10.5s

Created

almost 2 years ago

Input

width: 1536
height: 1536
prompt: Anthropomorphic cat dressed as a firefighter
negative_prompt
prior_guidance_scale: 4
num_images_per_prompt: 2
decoder_guidance_scale: 0
prior_num_inference_steps: 30
decoder_num_inference_steps: 12

{
  "width": 1536,
  "height": 1536,
  "prompt": "Anthropomorphic cat dressed as a firefighter",
  "negative_prompt": "",
  "prior_guidance_scale": 4,
  "num_images_per_prompt": 2,
  "decoder_guidance_scale": 0,
  "prior_num_inference_steps": 30,
  "decoder_num_inference_steps": 12
}

npm install replicate

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 cjwbw/wuerstchen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
  {
    input: {
      width: 1536,
      height: 1536,
      prompt: "Anthropomorphic cat dressed as a firefighter",
      negative_prompt: "",
      prior_guidance_scale: 4,
      num_images_per_prompt: 2,
      decoder_guidance_scale: 0,
      prior_num_inference_steps: 30,
      decoder_num_inference_steps: 12
    }
  }
);

// 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 cjwbw/wuerstchen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
    input={
        "width": 1536,
        "height": 1536,
        "prompt": "Anthropomorphic cat dressed as a firefighter",
        "negative_prompt": "",
        "prior_guidance_scale": 4,
        "num_images_per_prompt": 2,
        "decoder_guidance_scale": 0,
        "prior_num_inference_steps": 30,
        "decoder_num_inference_steps": 12
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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

Run cjwbw/wuerstchen 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": "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
    "input": {
      "width": 1536,
      "height": 1536,
      "prompt": "Anthropomorphic cat dressed as a firefighter",
      "negative_prompt": "",
      "prior_guidance_scale": 4,
      "num_images_per_prompt": 2,
      "decoder_guidance_scale": 0,
      "prior_num_inference_steps": 30,
      "decoder_num_inference_steps": 12
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-09-16T02:02:55.991788Z",
  "created_at": "2023-09-16T02:02:45.457545Z",
  "data_removed": false,
  "error": null,
  "id": "lsu7r7bbpgptzr5fhoq5io4pw4",
  "input": {
    "width": 1536,
    "height": 1536,
    "prompt": "Anthropomorphic cat dressed as a firefighter",
    "negative_prompt": "",
    "prior_guidance_scale": 4,
    "num_images_per_prompt": 2,
    "decoder_guidance_scale": 0,
    "prior_num_inference_steps": 30,
    "decoder_num_inference_steps": 12
  },
  "logs": "Using seed: 14945\n  0%|          | 0/29 [00:00<?, ?it/s]\n  3%|▎         | 1/29 [00:00<00:03,  7.21it/s]\n  7%|▋         | 2/29 [00:00<00:03,  8.14it/s]\n 10%|█         | 3/29 [00:00<00:03,  8.62it/s]\n 14%|█▍        | 4/29 [00:00<00:02,  8.86it/s]\n 17%|█▋        | 5/29 [00:00<00:02,  8.99it/s]\n 21%|██        | 6/29 [00:00<00:02,  9.07it/s]\n 24%|██▍       | 7/29 [00:00<00:02,  9.10it/s]\n 28%|██▊       | 8/29 [00:00<00:02,  9.13it/s]\n 31%|███       | 9/29 [00:01<00:02,  9.16it/s]\n 34%|███▍      | 10/29 [00:01<00:02,  9.16it/s]\n 38%|███▊      | 11/29 [00:01<00:01,  9.16it/s]\n 41%|████▏     | 12/29 [00:01<00:01,  9.17it/s]\n 45%|████▍     | 13/29 [00:01<00:01,  9.18it/s]\n 48%|████▊     | 14/29 [00:01<00:01,  9.19it/s]\n 52%|█████▏    | 15/29 [00:01<00:01,  9.18it/s]\n 55%|█████▌    | 16/29 [00:01<00:01,  9.18it/s]\n 59%|█████▊    | 17/29 [00:01<00:01,  9.18it/s]\n 62%|██████▏   | 18/29 [00:01<00:01,  9.19it/s]\n 66%|██████▌   | 19/29 [00:02<00:01,  9.20it/s]\n 69%|██████▉   | 20/29 [00:02<00:00,  9.18it/s]\n 72%|███████▏  | 21/29 [00:02<00:00,  9.17it/s]\n 76%|███████▌  | 22/29 [00:02<00:00,  9.18it/s]\n 79%|███████▉  | 23/29 [00:02<00:00,  9.18it/s]\n 83%|████████▎ | 24/29 [00:02<00:00,  9.19it/s]\n 86%|████████▌ | 25/29 [00:02<00:00,  8.93it/s]\n 90%|████████▉ | 26/29 [00:02<00:00,  9.00it/s]\n 93%|█████████▎| 27/29 [00:02<00:00,  9.06it/s]\n 97%|█████████▋| 28/29 [00:03<00:00,  9.10it/s]\n100%|██████████| 29/29 [00:03<00:00,  9.13it/s]\n100%|██████████| 29/29 [00:03<00:00,  9.07it/s]\n  0%|          | 0/12 [00:00<?, ?it/s]\n  8%|▊         | 1/12 [00:00<00:02,  4.71it/s]\n 17%|█▋        | 2/12 [00:00<00:02,  4.79it/s]\n 25%|██▌       | 3/12 [00:00<00:01,  4.81it/s]\n 33%|███▎      | 4/12 [00:00<00:01,  4.83it/s]\n 42%|████▏     | 5/12 [00:01<00:01,  4.83it/s]\n 50%|█████     | 6/12 [00:01<00:01,  4.84it/s]\n 58%|█████▊    | 7/12 [00:01<00:01,  4.84it/s]\n 67%|██████▋   | 8/12 [00:01<00:00,  4.84it/s]\n 75%|███████▌  | 9/12 [00:01<00:00,  4.83it/s]\n 83%|████████▎ | 10/12 [00:02<00:00,  4.83it/s]\n 92%|█████████▏| 11/12 [00:02<00:00,  4.83it/s]\n100%|██████████| 12/12 [00:02<00:00,  4.84it/s]\n100%|██████████| 12/12 [00:02<00:00,  4.83it/s]",
  "metrics": {
    "predict_time": 10.565402,
    "total_time": 10.534243
  },
  "output": [
    "https://replicate.delivery/pbxt/oZfwnHbhc9SrIyb0GqPkeZ3lbnfYdxnzR0BTplDGOERd2XJjA/out-0.png",
    "https://replicate.delivery/pbxt/JYZEud12pT7FPFV2MtZaSTx6lEr2Z0XMpPb8JBUSYu0zeVyIA/out-1.png"
  ],
  "started_at": "2023-09-16T02:02:45.426386Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/lsu7r7bbpgptzr5fhoq5io4pw4",
    "cancel": "https://api.replicate.com/v1/predictions/lsu7r7bbpgptzr5fhoq5io4pw4/cancel"
  },
  "version": "6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039"
}

Generated in

10.6 seconds

cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039

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Prediction

Model

ID

dyuleizbicn3jnusfnau72nafi

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

5.2s

Created

almost 2 years ago

Input

seed: null
width: 1536
height: 1536
prompt: Astronaut in the mushroom forest, psychedelic mood, astral figures, morning light, clear sky, extremely detailed
negative_prompt
prior_guidance_scale: 4
num_images_per_prompt: 1
decoder_guidance_scale: 0
prior_num_inference_steps: 60
decoder_num_inference_steps: 12

{
  "seed": null,
  "width": 1536,
  "height": 1536,
  "prompt": "Astronaut in the mushroom forest, psychedelic mood, astral figures, morning light, clear sky, extremely detailed",
  "negative_prompt": "",
  "prior_guidance_scale": 4,
  "num_images_per_prompt": 1,
  "decoder_guidance_scale": 0,
  "prior_num_inference_steps": 60,
  "decoder_num_inference_steps": 12
}

npm install replicate

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 cjwbw/wuerstchen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
  {
    input: {
      width: 1536,
      height: 1536,
      prompt: "Astronaut in the mushroom forest, psychedelic mood, astral figures, morning light, clear sky, extremely detailed",
      negative_prompt: "",
      prior_guidance_scale: 4,
      num_images_per_prompt: 1,
      decoder_guidance_scale: 0,
      prior_num_inference_steps: 60,
      decoder_num_inference_steps: 12
    }
  }
);

// 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 cjwbw/wuerstchen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
    input={
        "width": 1536,
        "height": 1536,
        "prompt": "Astronaut in the mushroom forest, psychedelic mood, astral figures, morning light, clear sky, extremely detailed",
        "negative_prompt": "",
        "prior_guidance_scale": 4,
        "num_images_per_prompt": 1,
        "decoder_guidance_scale": 0,
        "prior_num_inference_steps": 60,
        "decoder_num_inference_steps": 12
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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

Run cjwbw/wuerstchen 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": "cjwbw/wuerstchen:6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039",
    "input": {
      "width": 1536,
      "height": 1536,
      "prompt": "Astronaut in the mushroom forest, psychedelic mood, astral figures, morning light, clear sky, extremely detailed",
      "negative_prompt": "",
      "prior_guidance_scale": 4,
      "num_images_per_prompt": 1,
      "decoder_guidance_scale": 0,
      "prior_num_inference_steps": 60,
      "decoder_num_inference_steps": 12
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-09-16T02:07:48.237927Z",
  "created_at": "2023-09-16T02:07:43.025434Z",
  "data_removed": false,
  "error": null,
  "id": "dyuleizbicn3jnusfnau72nafi",
  "input": {
    "seed": null,
    "width": 1536,
    "height": 1536,
    "prompt": "Astronaut in the mushroom forest, psychedelic mood, astral figures, morning light, clear sky, extremely detailed",
    "negative_prompt": "",
    "prior_guidance_scale": 4,
    "num_images_per_prompt": 1,
    "decoder_guidance_scale": 0,
    "prior_num_inference_steps": 60,
    "decoder_num_inference_steps": 12
  },
  "logs": "Using seed: 20903\n  0%|          | 0/29 [00:00<?, ?it/s]\n  7%|▋         | 2/29 [00:00<00:02, 12.37it/s]\n 14%|█▍        | 4/29 [00:00<00:01, 14.70it/s]\n 21%|██        | 6/29 [00:00<00:01, 15.78it/s]\n 28%|██▊       | 8/29 [00:00<00:01, 16.35it/s]\n 34%|███▍      | 10/29 [00:00<00:01, 16.67it/s]\n 41%|████▏     | 12/29 [00:00<00:01, 16.87it/s]\n 48%|████▊     | 14/29 [00:00<00:00, 16.99it/s]\n 55%|█████▌    | 16/29 [00:00<00:00, 17.07it/s]\n 62%|██████▏   | 18/29 [00:01<00:00, 16.98it/s]\n 69%|██████▉   | 20/29 [00:01<00:00, 17.06it/s]\n 76%|███████▌  | 22/29 [00:01<00:00, 17.11it/s]\n 83%|████████▎ | 24/29 [00:01<00:00, 17.15it/s]\n 90%|████████▉ | 26/29 [00:01<00:00, 17.18it/s]\n 97%|█████████▋| 28/29 [00:01<00:00, 17.20it/s]\n100%|██████████| 29/29 [00:01<00:00, 16.74it/s]\n  0%|          | 0/12 [00:00<?, ?it/s]\n  8%|▊         | 1/12 [00:00<00:01,  9.64it/s]\n 17%|█▋        | 2/12 [00:00<00:01,  9.64it/s]\n 25%|██▌       | 3/12 [00:00<00:00,  9.64it/s]\n 33%|███▎      | 4/12 [00:00<00:00,  9.65it/s]\n 42%|████▏     | 5/12 [00:00<00:00,  9.66it/s]\n 50%|█████     | 6/12 [00:00<00:00,  9.66it/s]\n 58%|█████▊    | 7/12 [00:00<00:00,  9.65it/s]\n 67%|██████▋   | 8/12 [00:00<00:00,  9.65it/s]\n 75%|███████▌  | 9/12 [00:00<00:00,  9.66it/s]\n 83%|████████▎ | 10/12 [00:01<00:00,  9.66it/s]\n 92%|█████████▏| 11/12 [00:01<00:00,  9.50it/s]\n100%|██████████| 12/12 [00:01<00:00,  8.45it/s]\n100%|██████████| 12/12 [00:01<00:00,  9.28it/s]",
  "metrics": {
    "predict_time": 5.243501,
    "total_time": 5.212493
  },
  "output": [
    "https://replicate.delivery/pbxt/3P8SWv58bXI4E5qn7CCEZh5BteQIfwdMmc0R1qjR1aEzfXJjA/out-0.png"
  ],
  "started_at": "2023-09-16T02:07:42.994426Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/dyuleizbicn3jnusfnau72nafi",
    "cancel": "https://api.replicate.com/v1/predictions/dyuleizbicn3jnusfnau72nafi/cancel"
  },
  "version": "6a8baed32201ec714574e439aa57734acba760796731666bbd9470fefbd00039"
}

Generated in

5.3 seconds