Generates goo
Format of the output (image or video)
Default: "png"
Dimension of the output image
Default: 512
Height of the output image
Seed for the random number generator
Default: -1
Default: 1
Default: 3
Speed of the goo animation effect
Default: 2
Number of frames for video output (only used when format is mp4)
Default: 600
Frames per second for video output (only used when format is mp4)
Default: 60
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run replicate/goo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "replicate/goo:47d99faae8ef2b6acf728fb18a06a1435996a724372763551bae379f3d088080", { input: { fps: 60, seed: -1, depth: 3, scale: 2, speed: 2, width: 1024, format: "mp4", height: 1024, num_frames: 600 } } ); // 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.
pip install replicate
import replicate
output = replicate.run( "replicate/goo:47d99faae8ef2b6acf728fb18a06a1435996a724372763551bae379f3d088080", input={ "fps": 60, "seed": -1, "depth": 3, "scale": 2, "speed": 2, "width": 1024, "format": "mp4", "height": 1024, "num_frames": 600 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "replicate/goo:47d99faae8ef2b6acf728fb18a06a1435996a724372763551bae379f3d088080", "input": { "fps": 60, "seed": -1, "depth": 3, "scale": 2, "speed": 2, "width": 1024, "format": "mp4", "height": 1024, "num_frames": 600 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/replicate/goo@sha256:47d99faae8ef2b6acf728fb18a06a1435996a724372763551bae379f3d088080 \ -i 'fps=60' \ -i 'seed=-1' \ -i 'depth=3' \ -i 'scale=2' \ -i 'speed=2' \ -i 'width=1024' \ -i 'format="mp4"' \ -i 'height=1024' \ -i 'num_frames=600'
To learn more, take a look at the Cog documentation.
docker run -d -p 5000:5000 r8.im/replicate/goo@sha256:47d99faae8ef2b6acf728fb18a06a1435996a724372763551bae379f3d088080 curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "fps": 60, "seed": -1, "depth": 3, "scale": 2, "speed": 2, "width": 1024, "format": "mp4", "height": 1024, "num_frames": 600 } }' \ http://localhost:5000/predictions
docker run -d -p 5000:5000 r8.im/replicate/goo@sha256:47d99faae8ef2b6acf728fb18a06a1435996a724372763551bae379f3d088080
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "fps": 60, "seed": -1, "depth": 3, "scale": 2, "speed": 2, "width": 1024, "format": "mp4", "height": 1024, "num_frames": 600 } }' \ http://localhost:5000/predictions
{ "completed_at": "2025-03-12T04:06:34.466307Z", "created_at": "2025-03-12T04:06:18.044000Z", "data_removed": false, "error": null, "id": "g0nwqxs2qhrmc0cnh248x740v8", "input": { "fps": 60, "depth": 3, "scale": 2, "speed": 2, "width": 1024, "format": "mp4", "height": 1024, "num_frames": 600 }, "logs": null, "metrics": { "predict_time": 8.960117893, "total_time": 16.422307 }, "output": "https://replicate.delivery/xezq/cSkUWr5uQY5YP5nwuqfZyQUxPLd0ooBejWxp7oYwmJBKprXUA/output.mp4", "started_at": "2025-03-12T04:06:25.506189Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-4q3u7xunxut5puhbfhyrvmcuqwgwpkq5anjucf2z5kcsebs53fka", "get": "https://api.replicate.com/v1/predictions/g0nwqxs2qhrmc0cnh248x740v8", "cancel": "https://api.replicate.com/v1/predictions/g0nwqxs2qhrmc0cnh248x740v8/cancel" }, "version": "2b584b744053a34d738ef83ea0adef3fbf6c11ccb1cf6c270eace8c66cec624b" }
This output was created using a different version of the model, replicate/goo:2b584b74.
View more examples
This model runs on CPU hardware. We don't yet have enough runs of this model to provide performance information.
This model doesn't have a readme.
Classifies images with ResNet-50
Train your own custom Stable Diffusion model using a small set of images
A language model by Google for tasks like classification, summarization, and more
Transformers implementation of the LLaMA language model
A large language model by EleutherAI
This is a language model that can be used to obtain document embeddings suitable for downstream tasks like semantic search and clustering.
Train your own custom RVC model
Train subjects or styles faster than ever
Flux 2D Game Asset LoRA
This model is cold. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
This model runs on CPU hardware which costs $0.0001 per second. View more.