okaris/progen2:fe5e2691 – Run with an API on Replicate

Version

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okaris /progen2:fe5e2691

Playground API

Input

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

npx create-replicate --model=okaris/progen2

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 okaris/progen2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "okaris/progen2:fe5e269173bee130c418d8aa461dccd8401c58e47d22c37e31aaf094550b130f",
  {
    input: {
      p: 0.9,
      t: 0.8,
      fp16: true,
      model: "progen2-small",
      device: "cuda:0",
      sanity: true,
      context: "1",
      rng_seed: 42,
      max_length: 1024,
      num_samples: 2,
      rng_deterministic: true
    }
  }
);

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 okaris/progen2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "okaris/progen2:fe5e269173bee130c418d8aa461dccd8401c58e47d22c37e31aaf094550b130f",
    input={
        "p": 0.9,
        "t": 0.8,
        "fp16": True,
        "model": "progen2-small",
        "device": "cuda:0",
        "sanity": True,
        "context": "1",
        "rng_seed": 42,
        "max_length": 1024,
        "num_samples": 2,
        "rng_deterministic": True
    }
)
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 okaris/progen2 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": "fe5e269173bee130c418d8aa461dccd8401c58e47d22c37e31aaf094550b130f",
    "input": {
      "p": 0.9,
      "t": 0.8,
      "fp16": true,
      "model": "progen2-small",
      "device": "cuda:0",
      "sanity": true,
      "context": "1",
      "rng_seed": 42,
      "max_length": 1024,
      "num_samples": 2,
      "rng_deterministic": true
    }
  }' \
  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/okaris/progen2@sha256:fe5e269173bee130c418d8aa461dccd8401c58e47d22c37e31aaf094550b130f \
  -i 'p=0.9' \
  -i 't=0.8' \
  -i 'fp16=true' \
  -i 'model="progen2-small"' \
  -i 'device="cuda:0"' \
  -i 'sanity=true' \
  -i 'context="1"' \
  -i 'rng_seed=42' \
  -i 'max_length=1024' \
  -i 'num_samples=2' \
  -i 'rng_deterministic=true'

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 r8.im/okaris/progen2@sha256:fe5e269173bee130c418d8aa461dccd8401c58e47d22c37e31aaf094550b130f
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "p": 0.9,
      "t": 0.8,
      "fp16": true,
      "model": "progen2-small",
      "device": "cuda:0",
      "sanity": true,
      "context": "1",
      "rng_seed": 42,
      "max_length": 1024,
      "num_samples": 2,
      "rng_deterministic": true
    }
  }' \
  http://localhost:5000/predictions

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

Output

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