Prediction

ID

wasi5bidhfh3hhvsafuf3kdc5e

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.3s

Created

over 3 years ago

Input

model: afhqcat5k256x256-apa
noise_mode: const
num_images: "4"
truncation_psi: "1"

{
  "model": "afhqcat5k256x256-apa",
  "noise_mode": "const",
  "num_images": "4",
  "truncation_psi": "1"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
  {
    input: {
      model: "afhqcat5k256x256-apa",
      noise_mode: "const",
      num_images: "4",
      truncation_psi: "1"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
    input={
        "model": "afhqcat5k256x256-apa",
        "noise_mode": "const",
        "num_images": "4",
        "truncation_psi": "1"
    }
)

# The endlesssora/deceived 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/endlesssora/deceived/api#output-schema
    print(item)

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

Run endlesssora/deceived 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": "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
    "input": {
      "model": "afhqcat5k256x256-apa",
      "noise_mode": "const",
      "num_images": "4",
      "truncation_psi": "1"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.1 seconds

endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243

Prediction

Model

ID

cbwtdq5jd5ew7ky4egok3pzqji

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.4s

Created

over 3 years ago

Input

model: ffhq5k1024x1024-apa
noise_mode: const
num_images: "1"
truncation_psi: "1"

{
  "model": "ffhq5k1024x1024-apa",
  "noise_mode": "const",
  "num_images": "1",
  "truncation_psi": "1"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
  {
    input: {
      model: "ffhq5k1024x1024-apa",
      noise_mode: "const",
      num_images: "1",
      truncation_psi: "1"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
    input={
        "model": "ffhq5k1024x1024-apa",
        "noise_mode": "const",
        "num_images": "1",
        "truncation_psi": "1"
    }
)

# The endlesssora/deceived 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/endlesssora/deceived/api#output-schema
    print(item)

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

Run endlesssora/deceived 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": "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
    "input": {
      "model": "ffhq5k1024x1024-apa",
      "noise_mode": "const",
      "num_images": "1",
      "truncation_psi": "1"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.2 seconds

endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243

Prediction

Model

ID

lflflonjyzbv3kryvvt73qsuim

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.4s

Created

over 3 years ago

Input

model: ffhq70kfull256x256-apa
noise_mode: const
num_images: "4"
truncation_psi: "1"

{
  "model": "ffhq70kfull256x256-apa",
  "noise_mode": "const",
  "num_images": "4",
  "truncation_psi": "1"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
  {
    input: {
      model: "ffhq70kfull256x256-apa",
      noise_mode: "const",
      num_images: "4",
      truncation_psi: "1"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
    input={
        "model": "ffhq70kfull256x256-apa",
        "noise_mode": "const",
        "num_images": "4",
        "truncation_psi": "1"
    }
)

# The endlesssora/deceived 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/endlesssora/deceived/api#output-schema
    print(item)

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

Run endlesssora/deceived 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": "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
    "input": {
      "model": "ffhq70kfull256x256-apa",
      "noise_mode": "const",
      "num_images": "4",
      "truncation_psi": "1"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.2 seconds

endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243

Prediction

Model

ID

i4rhx7zmajbw5lyvt7joe44qnq

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.3s

Created

over 3 years ago

Input

model: anime5k256x256-apa
noise_mode: const
num_images: "4"
truncation_psi: "1"

{
  "model": "anime5k256x256-apa",
  "noise_mode": "const",
  "num_images": "4",
  "truncation_psi": "1"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
  {
    input: {
      model: "anime5k256x256-apa",
      noise_mode: "const",
      num_images: "4",
      truncation_psi: "1"
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
    input={
        "model": "anime5k256x256-apa",
        "noise_mode": "const",
        "num_images": "4",
        "truncation_psi": "1"
    }
)

# The endlesssora/deceived 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/endlesssora/deceived/api#output-schema
    print(item)

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

Run endlesssora/deceived 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": "endlesssora/deceived:87671bdafd70906256642ca5713fe029ec904368e9b25c7c63306b814a36a243",
    "input": {
      "model": "anime5k256x256-apa",
      "noise_mode": "const",
      "num_images": "4",
      "truncation_psi": "1"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.1 seconds