nateraw/stable-diffusion-videos:2d87f0f8 – Run with an API on Replicate

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nateraw /stable-diffusion-videos:2d87f0f8

Playground API

Input

prompts

string

Shift + Return to add a new line

Input prompts, separate each prompt with '|'.

Default: "a cat | a dog | a horse"

seeds

string

Shift + Return to add a new line

Random seed, separated with '|' to use different seeds for each of the prompt provided above. Leave blank to randomize the seed.

scheduler

string

Choose the scheduler

Default: "klms"

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps for each image generated from the prompt

Default: 50

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7.5

num_steps

integer

Steps for generating the interpolation video. Recommended to set to 3 or 5 for testing, then up it to 60-200 for better results.

Default: 50

fps

integer

(minimum: 5, maximum: 60)

Frame rate for the video.

Default: 15

Run this model in Node.js with one line of code:

npx create-replicate --model=nateraw/stable-diffusion-videos

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

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

Run nateraw/stable-diffusion-videos using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/stable-diffusion-videos:2d87f0f8bc282042002f8d24458bbf588eee5e8d8fffb6fbb10ed48d1dac409e",
  {
    input: {
      fps: 15,
      prompts: "a cat | a dog | a horse",
      num_steps: 50,
      scheduler: "klms",
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);
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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run nateraw/stable-diffusion-videos using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/stable-diffusion-videos:2d87f0f8bc282042002f8d24458bbf588eee5e8d8fffb6fbb10ed48d1dac409e",
    input={
        "fps": 15,
        "prompts": "a cat | a dog | a horse",
        "num_steps": 50,
        "scheduler": "klms",
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)
print(output)

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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run nateraw/stable-diffusion-videos 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": "2d87f0f8bc282042002f8d24458bbf588eee5e8d8fffb6fbb10ed48d1dac409e",
    "input": {
      "fps": 15,
      "prompts": "a cat | a dog | a horse",
      "num_steps": 50,
      "scheduler": "klms",
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

No output yet! Press "Submit" to start a prediction.