Prediction

luma/ray-flash-2-720p

Official model

luma/ray-flash-2-720p

ID

f5nnc0aq65rmc0cnjgjbrv5ftc

Status

Succeeded

Source

Web

Total duration

32.1s

Created

about 2 months ago

Input

loop
prompt: A cinematic anime character intimate closeup, she is sitting at a cafe on a busy city street in the morning, it is cold
duration: 5
aspect_ratio: 16:9

{
  "loop": false,
  "prompt": "A cinematic anime character intimate closeup, she is sitting at a cafe on a busy city street in the morning, it is cold",
  "duration": 5,
  "aspect_ratio": "16:9"
}

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 luma/ray-flash-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  loop: false,
  prompt: "A cinematic anime character intimate closeup, she is sitting at a cafe on a busy city street in the morning, it is cold",
  duration: 5,
  aspect_ratio: "16:9"
};

const output = await replicate.run("luma/ray-flash-2-720p", { input });

// 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 luma/ray-flash-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray-flash-2-720p",
    input={
        "loop": False,
        "prompt": "A cinematic anime character intimate closeup, she is sitting at a cafe on a busy city street in the morning, it is cold",
        "duration": 5,
        "aspect_ratio": "16:9"
    }
)
print(output)

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

Run luma/ray-flash-2-720p 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 $'{
    "input": {
      "loop": false,
      "prompt": "A cinematic anime character intimate closeup, she is sitting at a cafe on a busy city street in the morning, it is cold",
      "duration": 5,
      "aspect_ratio": "16:9"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray-flash-2-720p/predictions

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

Output

Generated in

32.1 seconds

Tweak it ShareReport

Prediction

luma/ray-flash-2-720p

Official model

luma/ray-flash-2-720p

ID

12j1d9xejsrme0cnjgkbfea0mm

Status

Succeeded

Source

Web

Total duration

31.5s

Created

about 2 months ago

Input

loop
prompt: A snow leopard crouched on a rocky ledge, staring directly at camera, snowflakes falling around it
duration: 5
aspect_ratio: 16:9

{
  "loop": false,
  "prompt": "A snow leopard crouched on a rocky ledge, staring directly at camera, snowflakes falling around it",
  "duration": 5,
  "aspect_ratio": "16:9"
}

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 luma/ray-flash-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  loop: false,
  prompt: "A snow leopard crouched on a rocky ledge, staring directly at camera, snowflakes falling around it",
  duration: 5,
  aspect_ratio: "16:9"
};

const output = await replicate.run("luma/ray-flash-2-720p", { input });

// 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 luma/ray-flash-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray-flash-2-720p",
    input={
        "loop": False,
        "prompt": "A snow leopard crouched on a rocky ledge, staring directly at camera, snowflakes falling around it",
        "duration": 5,
        "aspect_ratio": "16:9"
    }
)
print(output)

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

Run luma/ray-flash-2-720p 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 $'{
    "input": {
      "loop": false,
      "prompt": "A snow leopard crouched on a rocky ledge, staring directly at camera, snowflakes falling around it",
      "duration": 5,
      "aspect_ratio": "16:9"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray-flash-2-720p/predictions

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

Output

Generated in

31.5 seconds

Tweak it ShareReport

Prediction

luma/ray-flash-2-720p

Official model

luma/ray-flash-2-720p

ID

bgy8s1fg79rma0cnjgnt9psmhg

Status

Succeeded

Source

Web

Total duration

31.3s

Created

about 2 months ago

Input

loop
prompt: A polar bear swimming underwater
duration: 5
aspect_ratio: 16:9

{
  "loop": false,
  "prompt": "A polar bear swimming underwater",
  "duration": 5,
  "aspect_ratio": "16:9"
}

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 luma/ray-flash-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  loop: false,
  prompt: "A polar bear swimming underwater",
  duration: 5,
  aspect_ratio: "16:9"
};

const output = await replicate.run("luma/ray-flash-2-720p", { input });

// 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 luma/ray-flash-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray-flash-2-720p",
    input={
        "loop": False,
        "prompt": "A polar bear swimming underwater",
        "duration": 5,
        "aspect_ratio": "16:9"
    }
)
print(output)

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

Run luma/ray-flash-2-720p 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 $'{
    "input": {
      "loop": false,
      "prompt": "A polar bear swimming underwater",
      "duration": 5,
      "aspect_ratio": "16:9"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray-flash-2-720p/predictions

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

Output

Generated in

31.2 seconds

Tweak it ShareReport

luma / ray-flash-2-720p

Prediction

Input

Output

Prediction

Input

Output

Prediction

Input

Output

Logs (f5nnc0aq65rmc0cnjgjbrv5ftc)

Logs (12j1d9xejsrme0cnjgkbfea0mm)

Logs (bgy8s1fg79rma0cnjgnt9psmhg)