xl-sr / projected_gan

Generate Pokemons with Projected GAN

Cold

Public
9.7K runs
T4
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Run with an API

Playground API Examples README Versions

Prediction

xl-sr/projected_gan:9d43d5c4549bae1a687ae8113ab0a8844c0e9aed5fdc9d646263246955168bf7

Model

xl-sr/projected_gan:9d43d5c4

ivwoy2jar5hcvksz5whol56inu

Status

Succeeded

Source

Web

Hardware

–

Total duration

1m 39s

Created

over 3 years ago

Input

seed: 42
batch_size: 12

{
  "seed": 42,
  "batch_size": 12
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run xl-sr/projected_gan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "xl-sr/projected_gan:9d43d5c4549bae1a687ae8113ab0a8844c0e9aed5fdc9d646263246955168bf7",
  {
    input: {
      seed: 42,
      batch_size: 12
    }
  }
);

console.log(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

Import the client:

import replicate

Run xl-sr/projected_gan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "xl-sr/projected_gan:9d43d5c4549bae1a687ae8113ab0a8844c0e9aed5fdc9d646263246955168bf7",
    input={
        "seed": 42,
        "batch_size": 12
    }
)

# The xl-sr/projected_gan model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/xl-sr/projected_gan/api#output-schema
    print(item)

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

Run xl-sr/projected_gan 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": "xl-sr/projected_gan:9d43d5c4549bae1a687ae8113ab0a8844c0e9aed5fdc9d646263246955168bf7",
    "input": {
      "seed": 42,
      "batch_size": 12
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

5.3 seconds

Tweak it Share Report

Prediction

xl-sr/projected_gan:9d43d5c4549bae1a687ae8113ab0a8844c0e9aed5fdc9d646263246955168bf7

Model

xl-sr/projected_gan:9d43d5c4

iueno277r5gfbnmyptgttujv5y

Status

Succeeded

Source

Web

Hardware

–

Total duration

5.5s

Created

over 3 years ago

Input

seed: 43
batch_size: 12

{
  "seed": 43,
  "batch_size": 12
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run xl-sr/projected_gan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "xl-sr/projected_gan:9d43d5c4549bae1a687ae8113ab0a8844c0e9aed5fdc9d646263246955168bf7",
  {
    input: {
      seed: 43,
      batch_size: 12
    }
  }
);

console.log(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

Import the client:

import replicate

Run xl-sr/projected_gan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "xl-sr/projected_gan:9d43d5c4549bae1a687ae8113ab0a8844c0e9aed5fdc9d646263246955168bf7",
    input={
        "seed": 43,
        "batch_size": 12
    }
)

# The xl-sr/projected_gan model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/xl-sr/projected_gan/api#output-schema
    print(item)

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

Run xl-sr/projected_gan 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": "xl-sr/projected_gan:9d43d5c4549bae1a687ae8113ab0a8844c0e9aed5fdc9d646263246955168bf7",
    "input": {
      "seed": 43,
      "batch_size": 12
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

5.3 seconds

Tweak it Share Report

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xl-sr / projected_gan

Prediction

Input

Output

Prediction

Input

Output

Logs (ivwoy2jar5hcvksz5whol56inu)

Logs (iueno277r5gfbnmyptgttujv5y)