Prediction

luma/ray-2-720p

Official model

luma/ray-2-720p

ID

xdp12rh485rgc0cmmzxs8nqbzr

Status

Succeeded

Source

Web

Total duration

1m 46s

Created

3 months ago

Input

loop
prompt: A pirate ship in a raging sea
duration: 5
aspect_ratio: 16:9

{
  "loop": false,
  "prompt": "A pirate ship in a raging sea",
  "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-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 pirate ship in a raging sea",
  duration: 5,
  aspect_ratio: "16:9"
};

const output = await replicate.run("luma/ray-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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray-2-720p",
    input={
        "loop": False,
        "prompt": "A pirate ship in a raging sea",
        "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-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 pirate ship in a raging sea",
      "duration": 5,
      "aspect_ratio": "16:9"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray-2-720p/predictions

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

Output

Generated in

1 minute 46 seconds

Tweak it ShareReport

Prediction

luma/ray-2-720p

Official model

luma/ray-2-720p

ID

4ggp7jq0p1rga0cmn03rr5s10w

Status

Succeeded

Source

Web

Total duration

70.5s

Created

3 months ago by @luma

Input

loop
prompt: Insane camera flythrough of female surfer rideing massive wave at sunset, golden light streaming through the curl
duration: 5
aspect_ratio: 16:9

{
  "loop": false,
  "prompt": "Insane camera flythrough of female surfer rideing massive wave at sunset, golden light streaming through the curl",
  "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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  loop: false,
  prompt: "Insane camera flythrough of female surfer rideing massive wave at sunset, golden light streaming through the curl",
  duration: 5,
  aspect_ratio: "16:9"
};

const output = await replicate.run("luma/ray-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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray-2-720p",
    input={
        "loop": False,
        "prompt": "Insane camera flythrough of female surfer rideing massive wave at sunset, golden light streaming through the curl",
        "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-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": "Insane camera flythrough of female surfer rideing massive wave at sunset, golden light streaming through the curl",
      "duration": 5,
      "aspect_ratio": "16:9"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray-2-720p/predictions

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

Output

Generated in

70.5 seconds

Tweak it ShareReport

Prediction

luma/ray-2-720p

Official model

luma/ray-2-720p

ID

xb1r0ederxrge0cmn04874g3y4

Status

Succeeded

Source

Web

Total duration

71.1s

Created

3 months ago

Input

loop
prompt: Mind-bending dolly zoom on motocross rider soaring through sunset
duration: 5
aspect_ratio: 16:9

{
  "loop": false,
  "prompt": "Mind-bending dolly zoom on motocross rider soaring through sunset",
  "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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  loop: false,
  prompt: "Mind-bending dolly zoom on motocross rider soaring through sunset",
  duration: 5,
  aspect_ratio: "16:9"
};

const output = await replicate.run("luma/ray-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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray-2-720p",
    input={
        "loop": False,
        "prompt": "Mind-bending dolly zoom on motocross rider soaring through sunset",
        "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-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": "Mind-bending dolly zoom on motocross rider soaring through sunset",
      "duration": 5,
      "aspect_ratio": "16:9"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray-2-720p/predictions

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

Output

Generated in

71.1 seconds

Tweak it ShareReport

Prediction

luma/ray-2-720p

Official model

luma/ray-2-720p

ID

1yzxc6j7tsrgc0cmn069y5k1tc

Status

Succeeded

Source

Web

Total duration

80.2s

Created

3 months ago

Input

loop
prompt: Aggressive camera circles Russian ballet performance in grand setting
duration: 5
aspect_ratio: 16:9

{
  "loop": false,
  "prompt": "Aggressive camera circles Russian ballet performance in grand setting",
  "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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  loop: false,
  prompt: "Aggressive camera circles Russian ballet performance in grand setting",
  duration: 5,
  aspect_ratio: "16:9"
};

const output = await replicate.run("luma/ray-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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray-2-720p",
    input={
        "loop": False,
        "prompt": "Aggressive camera circles Russian ballet performance in grand setting",
        "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-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": "Aggressive camera circles Russian ballet performance in grand setting",
      "duration": 5,
      "aspect_ratio": "16:9"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray-2-720p/predictions

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

Output

Generated in

80.2 seconds

Tweak it ShareReport

Prediction

luma/ray-2-720p

Official model

luma/ray-2-720p

ID

5597yschg1rg80cmn05vtg6q0r

Status

Succeeded

Source

Web

Total duration

1m 49s

Created

3 months ago

Input

loop
prompt: Chaotic camera ducks between breakdancers battling, spotlights pulsing overhead
duration: 5
aspect_ratio: 16:9

{
  "loop": false,
  "prompt": "Chaotic camera ducks between breakdancers battling, spotlights pulsing overhead",
  "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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  loop: false,
  prompt: "Chaotic camera ducks between breakdancers battling, spotlights pulsing overhead",
  duration: 5,
  aspect_ratio: "16:9"
};

const output = await replicate.run("luma/ray-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-2-720p using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "luma/ray-2-720p",
    input={
        "loop": False,
        "prompt": "Chaotic camera ducks between breakdancers battling, spotlights pulsing overhead",
        "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-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": "Chaotic camera ducks between breakdancers battling, spotlights pulsing overhead",
      "duration": 5,
      "aspect_ratio": "16:9"
    }
  }' \
  https://api.replicate.com/v1/models/luma/ray-2-720p/predictions

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

Output

Generated in

1 minute 49 seconds

Tweak it ShareReport

luma / ray-2-720p

Prediction

Input

Output

Prediction

Input

Output

Prediction

Input

Output

Prediction

Input

Output

Prediction

Input

Output

Logs (xdp12rh485rgc0cmmzxs8nqbzr)

Logs (4ggp7jq0p1rga0cmn03rr5s10w)

Logs (xb1r0ederxrge0cmn04874g3y4)

Logs (1yzxc6j7tsrgc0cmn069y5k1tc)

Logs (5597yschg1rg80cmn05vtg6q0r)