lime-j/deepfspis:d011e261 – Run with an API on Replicate

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lime-j /deepfspis:d011e261

Playground API

Input

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

npx create-replicate --model=lime-j/deepfspis

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 lime-j/deepfspis using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lime-j/deepfspis:d011e261feff2cb38f59cdcbe8d49b744f712e5d83b55ebde2c7338048017ea5",
  {
    input: {
      lamb: 0.59,
      image: "https://replicate.delivery/pbxt/IRFfPEoQmXvT0mwBgBpxBw7MDakQxwZ1TCWmMyZ04gNNrQOI/00003.png"
    }
  }
);
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 lime-j/deepfspis using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lime-j/deepfspis:d011e261feff2cb38f59cdcbe8d49b744f712e5d83b55ebde2c7338048017ea5",
    input={
        "lamb": 0.59,
        "image": "https://replicate.delivery/pbxt/IRFfPEoQmXvT0mwBgBpxBw7MDakQxwZ1TCWmMyZ04gNNrQOI/00003.png"
    }
)
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 lime-j/deepfspis 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": "d011e261feff2cb38f59cdcbe8d49b744f712e5d83b55ebde2c7338048017ea5",
    "input": {
      "lamb": 0.59,
      "image": "https://replicate.delivery/pbxt/IRFfPEoQmXvT0mwBgBpxBw7MDakQxwZ1TCWmMyZ04gNNrQOI/00003.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

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/lime-j/deepfspis@sha256:d011e261feff2cb38f59cdcbe8d49b744f712e5d83b55ebde2c7338048017ea5 \
  -i 'lamb=0.59' \
  -i 'image="https://replicate.delivery/pbxt/IRFfPEoQmXvT0mwBgBpxBw7MDakQxwZ1TCWmMyZ04gNNrQOI/00003.png"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/lime-j/deepfspis@sha256:d011e261feff2cb38f59cdcbe8d49b744f712e5d83b55ebde2c7338048017ea5
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "lamb": 0.59,
      "image": "https://replicate.delivery/pbxt/IRFfPEoQmXvT0mwBgBpxBw7MDakQxwZ1TCWmMyZ04gNNrQOI/00003.png"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

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