Prediction

prunaai/flux.1-juiced:c459eddd07cc0d4069da3fb196fb64be33deee65ca1fa2380d3f0acb401fa787

Model

prunaai/flux.1-juiced:c459eddd

ID

8kagzx3ynhrm80cnw4cbwxt57m

Status

Succeeded

Source

Web

Hardware

H100

Total duration

1.9s

Created

about 1 month ago

Input

seed: 42
prompt: a cat jumping in the air to catch a bird
guidance: 3
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
prompt_strength: 0.8
num_inference_steps: 28

{
  "seed": 42,
  "prompt": "a cat jumping in the air to catch a bird",
  "guidance": 3,
  "go_fast_af": true,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "prompt_strength": 0.8,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:c459eddd07cc0d4069da3fb196fb64be33deee65ca1fa2380d3f0acb401fa787",
  {
    input: {
      seed: 42,
      prompt: "a cat jumping in the air to catch a bird",
      guidance: 3,
      go_fast_af: true,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      prompt_strength: 0.8,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:c459eddd07cc0d4069da3fb196fb64be33deee65ca1fa2380d3f0acb401fa787",
    input={
        "seed": 42,
        "prompt": "a cat jumping in the air to catch a bird",
        "guidance": 3,
        "go_fast_af": True,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "prompt_strength": 0.8,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "c459eddd07cc0d4069da3fb196fb64be33deee65ca1fa2380d3f0acb401fa787",
    "input": {
      "seed": 42,
      "prompt": "a cat jumping in the air to catch a bird",
      "guidance": 3,
      "go_fast_af": true,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "prompt_strength": 0.8,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.9 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:c459eddd07cc0d4069da3fb196fb64be33deee65ca1fa2380d3f0acb401fa787

Model

prunaai/flux.1-juiced:c459eddd

ID

8kagzx3ynhrm80cnw4cbwxt57m

Status

Succeeded

Source

Web

Hardware

H100

Total duration

1.9s

Created

about 1 month ago

Input

seed: 42
prompt: a cat jumping in the air to catch a bird
guidance: 3
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
prompt_strength: 0.8
num_inference_steps: 28

{
  "seed": 42,
  "prompt": "a cat jumping in the air to catch a bird",
  "guidance": 3,
  "go_fast_af": true,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "prompt_strength": 0.8,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:c459eddd07cc0d4069da3fb196fb64be33deee65ca1fa2380d3f0acb401fa787",
  {
    input: {
      seed: 42,
      prompt: "a cat jumping in the air to catch a bird",
      guidance: 3,
      go_fast_af: true,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      prompt_strength: 0.8,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:c459eddd07cc0d4069da3fb196fb64be33deee65ca1fa2380d3f0acb401fa787",
    input={
        "seed": 42,
        "prompt": "a cat jumping in the air to catch a bird",
        "guidance": 3,
        "go_fast_af": True,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "prompt_strength": 0.8,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "c459eddd07cc0d4069da3fb196fb64be33deee65ca1fa2380d3f0acb401fa787",
    "input": {
      "seed": 42,
      "prompt": "a cat jumping in the air to catch a bird",
      "guidance": 3,
      "go_fast_af": true,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "prompt_strength": 0.8,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.9 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:fdf1e8a9ac75b719294613e5c211d4c099135da1a8488fa72f042fa20bcd9c74

Model

prunaai/flux.1-juiced:fdf1e8a9

ID

jm3bcvz2c9rm80cnw9xsnx4qzw

Status

Succeeded

Source

Web

Hardware

H100

Total duration

2.0s

Created

about 1 month ago

Input

seed: 41
prompt: black forest gateau cake spelling out the words "FLUX CHEETAH", tasty, food photography, dynamic shot
guidance: 3.5
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
prompt_strength: 0.8
num_inference_steps: 28

{
  "seed": 41,
  "prompt": "black forest gateau cake spelling out the words \"FLUX CHEETAH\", tasty, food photography, dynamic shot",
  "guidance": 3.5,
  "go_fast_af": true,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "prompt_strength": 0.8,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:fdf1e8a9ac75b719294613e5c211d4c099135da1a8488fa72f042fa20bcd9c74",
  {
    input: {
      seed: 41,
      prompt: "black forest gateau cake spelling out the words \"FLUX CHEETAH\", tasty, food photography, dynamic shot",
      guidance: 3.5,
      go_fast_af: true,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      prompt_strength: 0.8,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:fdf1e8a9ac75b719294613e5c211d4c099135da1a8488fa72f042fa20bcd9c74",
    input={
        "seed": 41,
        "prompt": "black forest gateau cake spelling out the words \"FLUX CHEETAH\", tasty, food photography, dynamic shot",
        "guidance": 3.5,
        "go_fast_af": True,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "prompt_strength": 0.8,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "fdf1e8a9ac75b719294613e5c211d4c099135da1a8488fa72f042fa20bcd9c74",
    "input": {
      "seed": 41,
      "prompt": "black forest gateau cake spelling out the words \\"FLUX CHEETAH\\", tasty, food photography, dynamic shot",
      "guidance": 3.5,
      "go_fast_af": true,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "prompt_strength": 0.8,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.0 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:ef5a843551246c526805e90a24a994ac0b007808aa3eed82c86c370e2a85371c

Model

prunaai/flux.1-juiced:ef5a8435

ID

54wc8waqrnrm80cnwaavmvf0hc

Status

Succeeded

Source

Web

Hardware

H100

Total duration

2.0s

Created

about 1 month ago

Input

seed: 42
prompt: black forest gateau cake spelling out the words "FLUX DEV", tasty, food photography, dynamic shot
guidance: 3.5
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 42,
  "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
  "guidance": 3.5,
  "go_fast_af": true,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:ef5a843551246c526805e90a24a994ac0b007808aa3eed82c86c370e2a85371c",
  {
    input: {
      seed: 42,
      prompt: "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
      guidance: 3.5,
      go_fast_af: true,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:ef5a843551246c526805e90a24a994ac0b007808aa3eed82c86c370e2a85371c",
    input={
        "seed": 42,
        "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
        "guidance": 3.5,
        "go_fast_af": True,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "ef5a843551246c526805e90a24a994ac0b007808aa3eed82c86c370e2a85371c",
    "input": {
      "seed": 42,
      "prompt": "black forest gateau cake spelling out the words \\"FLUX DEV\\", tasty, food photography, dynamic shot",
      "guidance": 3.5,
      "go_fast_af": true,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.0 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5

Model

prunaai/flux.1-juiced:40395798

ID

3s8bqm5q8drma0cnwadv7w8cpr

Status

Succeeded

Source

Web

Hardware

H100

Total duration

0.5s

Created

about 1 month ago

Input

seed: 0
prompt: black forest gateau cake spelling out the words "FLUX DEV", tasty, food photography, dynamic shot
guidance: 3.5
go_faster
go_fast_af
image_size: 512
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 0,
  "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
  "guidance": 3.5,
  "go_faster": false,
  "go_fast_af": true,
  "image_size": 512,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
  {
    input: {
      seed: 0,
      prompt: "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
      guidance: 3.5,
      go_faster: false,
      go_fast_af: true,
      image_size: 512,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    input={
        "seed": 0,
        "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
        "guidance": 3.5,
        "go_faster": False,
        "go_fast_af": True,
        "image_size": 512,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    "input": {
      "seed": 0,
      "prompt": "black forest gateau cake spelling out the words \\"FLUX DEV\\", tasty, food photography, dynamic shot",
      "guidance": 3.5,
      "go_faster": false,
      "go_fast_af": true,
      "image_size": 512,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.5 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5

Model

prunaai/flux.1-juiced:40395798

ID

fcvtbvdp1srm80cnwaev618k4w

Status

Succeeded

Source

Web

Hardware

H100

Total duration

1.5s

Created

about 1 month ago

Input

seed: 0
prompt: black forest gateau cake spelling out the words "FLUX DEV", tasty, food photography, dynamic shot
guidance: 3.5
go_faster
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 0,
  "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
  "guidance": 3.5,
  "go_faster": false,
  "go_fast_af": true,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
  {
    input: {
      seed: 0,
      prompt: "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
      guidance: 3.5,
      go_faster: false,
      go_fast_af: true,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    input={
        "seed": 0,
        "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
        "guidance": 3.5,
        "go_faster": False,
        "go_fast_af": True,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    "input": {
      "seed": 0,
      "prompt": "black forest gateau cake spelling out the words \\"FLUX DEV\\", tasty, food photography, dynamic shot",
      "guidance": 3.5,
      "go_faster": false,
      "go_fast_af": true,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.5 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5

Model

prunaai/flux.1-juiced:40395798

ID

3e4mckf34xrme0cnwaer0k2d7w

Status

Succeeded

Source

Web

Hardware

H100

Total duration

2.0s

Created

about 1 month ago

Input

seed: 0
prompt: black forest gateau cake spelling out the words "FLUX DEV", tasty, food photography, dynamic shot
guidance: 3.5
go_faster
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 0,
  "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
  "guidance": 3.5,
  "go_faster": true,
  "go_fast_af": false,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
  {
    input: {
      seed: 0,
      prompt: "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
      guidance: 3.5,
      go_faster: true,
      go_fast_af: false,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    input={
        "seed": 0,
        "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
        "guidance": 3.5,
        "go_faster": True,
        "go_fast_af": False,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    "input": {
      "seed": 0,
      "prompt": "black forest gateau cake spelling out the words \\"FLUX DEV\\", tasty, food photography, dynamic shot",
      "guidance": 3.5,
      "go_faster": true,
      "go_fast_af": false,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.0 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5

Model

prunaai/flux.1-juiced:40395798

ID

7wmcbrsnfdrma0cnwahttbatbm

Status

Succeeded

Source

Web

Hardware

H100

Total duration

1.5s

Created

about 1 month ago

Input

seed: -1
prompt: a tiny astronaut hatching from an egg on the moon
guidance: 3.5
go_faster
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": -1,
  "prompt": "a tiny astronaut hatching from an egg on the moon",
  "guidance": 3.5,
  "go_faster": false,
  "go_fast_af": true,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
  {
    input: {
      seed: -1,
      prompt: "a tiny astronaut hatching from an egg on the moon",
      guidance: 3.5,
      go_faster: false,
      go_fast_af: true,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    input={
        "seed": -1,
        "prompt": "a tiny astronaut hatching from an egg on the moon",
        "guidance": 3.5,
        "go_faster": False,
        "go_fast_af": True,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    "input": {
      "seed": -1,
      "prompt": "a tiny astronaut hatching from an egg on the moon",
      "guidance": 3.5,
      "go_faster": false,
      "go_fast_af": true,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.5 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5

Model

prunaai/flux.1-juiced:40395798

ID

vqfmppk74nrm80cnwahs0973k4

Status

Succeeded

Source

Web

Hardware

H100

Total duration

2.0s

Created

about 1 month ago by @prunaai

Input

seed: -1
prompt: a tiny astronaut hatching from an egg on the moon
guidance: 3.5
go_faster
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": -1,
  "prompt": "a tiny astronaut hatching from an egg on the moon",
  "guidance": 3.5,
  "go_faster": true,
  "go_fast_af": false,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
  {
    input: {
      seed: -1,
      prompt: "a tiny astronaut hatching from an egg on the moon",
      guidance: 3.5,
      go_faster: true,
      go_fast_af: false,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    input={
        "seed": -1,
        "prompt": "a tiny astronaut hatching from an egg on the moon",
        "guidance": 3.5,
        "go_faster": True,
        "go_fast_af": False,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    "input": {
      "seed": -1,
      "prompt": "a tiny astronaut hatching from an egg on the moon",
      "guidance": 3.5,
      "go_faster": true,
      "go_fast_af": false,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.0 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5

Model

prunaai/flux.1-juiced:40395798

ID

hv6d8f7y45rm80cny6ybc376cw

Status

Succeeded

Source

Web

Hardware

H100

Total duration

1.5s

Created

about 1 month ago

Input

seed: 1
prompt: An anime illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.
guidance: 3.5
go_faster
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 1,
  "prompt": "An anime illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.",
  "guidance": 3.5,
  "go_faster": false,
  "go_fast_af": true,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
  {
    input: {
      seed: 1,
      prompt: "An anime illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.",
      guidance: 3.5,
      go_faster: false,
      go_fast_af: true,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    input={
        "seed": 1,
        "prompt": "An anime illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.",
        "guidance": 3.5,
        "go_faster": False,
        "go_fast_af": True,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    "input": {
      "seed": 1,
      "prompt": "An anime illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.",
      "guidance": 3.5,
      "go_faster": false,
      "go_fast_af": true,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.5 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5

Model

prunaai/flux.1-juiced:40395798

ID

tsgxnf6e71rma0cny6ysm2s338

Status

Succeeded

Source

Web

Hardware

H100

Total duration

1.5s

Created

about 1 month ago

Input

seed: 1
prompt: A ghibli style illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.
guidance: 3.5
go_faster
go_fast_af
image_size: 1024
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 1,
  "prompt": "A ghibli style illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.",
  "guidance": 3.5,
  "go_faster": false,
  "go_fast_af": true,
  "image_size": 1024,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
  {
    input: {
      seed: 1,
      prompt: "A ghibli style illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.",
      guidance: 3.5,
      go_faster: false,
      go_fast_af: true,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    input={
        "seed": 1,
        "prompt": "A ghibli style illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.",
        "guidance": 3.5,
        "go_faster": False,
        "go_fast_af": True,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    "input": {
      "seed": 1,
      "prompt": "A ghibli style illustration of Sydney Opera House sitting next to Eiffel tower, under a blue night sky of roiling energy, exploding yellow stars, and radiating swirls of blue.",
      "guidance": 3.5,
      "go_faster": false,
      "go_fast_af": true,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.5 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410

Model

prunaai/flux.1-juiced:58977759

ID

6edde215mxrme0cp1z5vpxanbw

Status

Succeeded

Source

Web

Hardware

H100

Total duration

2.3s

Created

26 days ago

Input

seed: -1
prompt: a purple cheetah holding a sign that says "Hello from Pruna"
guidance: 3.5
image_size: 1024
speed_mode: Juiced 🔥 (default)
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": -1,
  "prompt": "a purple cheetah holding a sign that says \"Hello from Pruna\"",
  "guidance": 3.5,
  "image_size": 1024,
  "speed_mode": "Juiced 🔥 (default)",
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
  {
    input: {
      seed: -1,
      prompt: "a purple cheetah holding a sign that says \"Hello from Pruna\"",
      guidance: 3.5,
      image_size: 1024,
      speed_mode: "Juiced 🔥 (default)",
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
    input={
        "seed": -1,
        "prompt": "a purple cheetah holding a sign that says \"Hello from Pruna\"",
        "guidance": 3.5,
        "image_size": 1024,
        "speed_mode": "Juiced 🔥 (default)",
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
    "input": {
      "seed": -1,
      "prompt": "a purple cheetah holding a sign that says \\"Hello from Pruna\\"",
      "guidance": 3.5,
      "image_size": 1024,
      "speed_mode": "Juiced 🔥 (default)",
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.3 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410

Model

prunaai/flux.1-juiced:58977759

ID

635wxchzqhrm80cp1z7989ypmr

Status

Succeeded

Source

Web

Hardware

H100

Total duration

2.3s

Created

26 days ago

Input

seed: 2
prompt: a purple cheetah holding a sign that says "Hello from Pruna"
guidance: 3.5
image_size: 1024
speed_mode: Juiced 🔥 (default)
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 2,
  "prompt": "a purple cheetah holding a sign that says \"Hello from Pruna\"",
  "guidance": 3.5,
  "image_size": 1024,
  "speed_mode": "Juiced 🔥 (default)",
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
  {
    input: {
      seed: 2,
      prompt: "a purple cheetah holding a sign that says \"Hello from Pruna\"",
      guidance: 3.5,
      image_size: 1024,
      speed_mode: "Juiced 🔥 (default)",
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
    input={
        "seed": 2,
        "prompt": "a purple cheetah holding a sign that says \"Hello from Pruna\"",
        "guidance": 3.5,
        "image_size": 1024,
        "speed_mode": "Juiced 🔥 (default)",
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
    "input": {
      "seed": 2,
      "prompt": "a purple cheetah holding a sign that says \\"Hello from Pruna\\"",
      "guidance": 3.5,
      "image_size": 1024,
      "speed_mode": "Juiced 🔥 (default)",
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.3 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410

Model

prunaai/flux.1-juiced:58977759

ID

vr3c5mfwesrma0cp1z782r4404

Status

Succeeded

Source

Web

Hardware

H100

Total duration

4.7s

Created

26 days ago

Input

seed: 2
prompt: a purple cheetah holding a sign that says "pip install pruna"
guidance: 3.5
image_size: 1024
speed_mode: Juiced 🔥 (default)
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 2,
  "prompt": "a purple cheetah holding a sign that says \"pip install pruna\"",
  "guidance": 3.5,
  "image_size": 1024,
  "speed_mode": "Juiced 🔥 (default)",
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
  {
    input: {
      seed: 2,
      prompt: "a purple cheetah holding a sign that says \"pip install pruna\"",
      guidance: 3.5,
      image_size: 1024,
      speed_mode: "Juiced 🔥 (default)",
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
    input={
        "seed": 2,
        "prompt": "a purple cheetah holding a sign that says \"pip install pruna\"",
        "guidance": 3.5,
        "image_size": 1024,
        "speed_mode": "Juiced 🔥 (default)",
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "58977759ff2870cc010597ae75f4d87866d169b248e02b6e86c4e1bf8afe2410",
    "input": {
      "seed": 2,
      "prompt": "a purple cheetah holding a sign that says \\"pip install pruna\\"",
      "guidance": 3.5,
      "image_size": 1024,
      "speed_mode": "Juiced 🔥 (default)",
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.3 seconds

Tweak it Share Report

Prediction

prunaai/flux.1-juiced:19335b8316dee4169b78fd08cdb91db5678ae2c56a96d60d000dbb46e555c1ea

Model

prunaai/flux.1-juiced:19335b83

ID

3ka1csf1zdrm80cp2mh9fwvx00

Status

Succeeded

Source

Web

Hardware

H100

Total duration

2.3s

Created

25 days ago

Input

seed: 2
prompt: a purple cheetah holding a sign that says "pip install pruna"
guidance: 3.5
image_size: 1024
speed_mode: Juiced 🔥 (default)
aspect_ratio: 1:1
output_format: webp
output_quality: 80
num_inference_steps: 28

{
  "seed": 2,
  "prompt": "a purple cheetah holding a sign that says \"pip install pruna\"",
  "guidance": 3.5,
  "image_size": 1024,
  "speed_mode": "Juiced 🔥 (default)",
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "output_quality": 80,
  "num_inference_steps": 28
}

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 prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-juiced:19335b8316dee4169b78fd08cdb91db5678ae2c56a96d60d000dbb46e555c1ea",
  {
    input: {
      seed: 2,
      prompt: "a purple cheetah holding a sign that says \"pip install pruna\"",
      guidance: 3.5,
      image_size: 1024,
      speed_mode: "Juiced 🔥 (default)",
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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

Import the client:

import replicate

Run prunaai/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:19335b8316dee4169b78fd08cdb91db5678ae2c56a96d60d000dbb46e555c1ea",
    input={
        "seed": 2,
        "prompt": "a purple cheetah holding a sign that says \"pip install pruna\"",
        "guidance": 3.5,
        "image_size": 1024,
        "speed_mode": "Juiced 🔥 (default)",
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run prunaai/flux.1-juiced 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": "19335b8316dee4169b78fd08cdb91db5678ae2c56a96d60d000dbb46e555c1ea",
    "input": {
      "seed": 2,
      "prompt": "a purple cheetah holding a sign that says \\"pip install pruna\\"",
      "guidance": 3.5,
      "image_size": 1024,
      "speed_mode": "Juiced 🔥 (default)",
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.3 seconds

Tweak it Share Report