Prediction

ID

zvycwf2rp5bprmcmhuzyt5yy7a

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.7s

Created

almost 3 years ago

Input

prompt: A crayon painting of barack Obama
num_outputs: 3

{
  "prompt": "A crayon painting of barack Obama",
  "num_outputs": 3
}

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 arielreplicate/paella_fast_text2image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
  {
    input: {
      prompt: "A crayon painting of barack Obama",
      num_outputs: 3
    }
  }
);

// 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.

Tweak it Iterate in playground ShareReport

pip install replicate

Import the client:

import replicate

Run arielreplicate/paella_fast_text2image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
    input={
        "prompt": "A crayon painting of barack Obama",
        "num_outputs": 3
    }
)

# 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 arielreplicate/paella_fast_text2image 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": "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
    "input": {
      "prompt": "A crayon painting of barack Obama",
      "num_outputs": 3
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/arielreplicate/paella_fast_text2image@sha256:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da \
  -i 'prompt="A crayon painting of barack Obama"' \
  -i 'num_outputs=3'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/arielreplicate/paella_fast_text2image@sha256:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "prompt": "A crayon painting of barack Obama",
      "num_outputs": 3
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

Generated in

2.6 seconds

Prediction

arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da

Model

ID

puknid3trzb5ndxxlywanhnecy

Status

Succeeded

Source

Web

Hardware

–

Total duration

5.2s

Created

almost 3 years ago

Input

prompt: A beautiful bavarian village with the alps in the backtground.
num_outputs: 6

{
  "prompt": "A beautiful bavarian village with the alps in the backtground.",
  "num_outputs": 6
}

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 arielreplicate/paella_fast_text2image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
  {
    input: {
      prompt: "A beautiful bavarian village with the alps in the backtground.",
      num_outputs: 6
    }
  }
);

// 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.

Tweak it Iterate in playground ShareReport

pip install replicate

Import the client:

import replicate

Run arielreplicate/paella_fast_text2image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
    input={
        "prompt": "A beautiful bavarian village with the alps in the backtground.",
        "num_outputs": 6
    }
)

# 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 arielreplicate/paella_fast_text2image 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": "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
    "input": {
      "prompt": "A beautiful bavarian village with the alps in the backtground.",
      "num_outputs": 6
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/arielreplicate/paella_fast_text2image@sha256:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da \
  -i 'prompt="A beautiful bavarian village with the alps in the backtground."' \
  -i 'num_outputs=6'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/arielreplicate/paella_fast_text2image@sha256:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "prompt": "A beautiful bavarian village with the alps in the backtground.",
      "num_outputs": 6
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

Generated in

5.2 seconds

Prediction

arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da

Model

ID

7xzx3qr3snh5dfppuz6bm5fisu

Status

Succeeded

Source

Web

Hardware

–

Total duration

5.3s

Created

almost 3 years ago

Input

prompt: Highly detailed photograph of darth vader. artstation
num_outputs: 6

{
  "prompt": "Highly detailed photograph of darth vader. artstation",
  "num_outputs": 6
}

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 arielreplicate/paella_fast_text2image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
  {
    input: {
      prompt: "Highly detailed photograph of darth vader. artstation",
      num_outputs: 6
    }
  }
);

// 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.

Tweak it Iterate in playground ShareReport

pip install replicate

Import the client:

import replicate

Run arielreplicate/paella_fast_text2image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
    input={
        "prompt": "Highly detailed photograph of darth vader. artstation",
        "num_outputs": 6
    }
)

# 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 arielreplicate/paella_fast_text2image 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": "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
    "input": {
      "prompt": "Highly detailed photograph of darth vader. artstation",
      "num_outputs": 6
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/arielreplicate/paella_fast_text2image@sha256:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da \
  -i 'prompt="Highly detailed photograph of darth vader. artstation"' \
  -i 'num_outputs=6'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/arielreplicate/paella_fast_text2image@sha256:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "prompt": "Highly detailed photograph of darth vader. artstation",
      "num_outputs": 6
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

Generated in

5.3 seconds

Prediction

arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da

Model

ID

oohalfvtxfdppi5lqv7s7kep64

Status

Succeeded

Source

Web

Hardware

–

Total duration

5.0s

Created

almost 3 years ago

Input

prompt: An oil painting of a cute german shepard
num_outputs: 6

{
  "prompt": "An oil painting of a cute german shepard",
  "num_outputs": 6
}

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 arielreplicate/paella_fast_text2image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "arielreplicate/paella_fast_text2image:481ea32fad34b0df3b74151c74e7572f7759d9712bbea169b4a75fba780324da",
  {
    input: {
      prompt: "An oil painting of a cute german shepard",
      num_outputs: 6
    }
  }
);

// 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.