daanelson/sd-21-fp16 – Run with an API on Replicate

daanelson / sd-21-fp16

Cold

Public
29 runs
T4

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=daanelson/sd-21-fp16

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 daanelson/sd-21-fp16 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "daanelson/sd-21-fp16:77ac4b275220676416d58e3fae95ddba590d9b9289222ca2be992a399a955a90",
  {
    input: {
      width: 768,
      height: 768,
      prompt: "a photo of an astronaut riding a horse on mars",
      scheduler: "DPMSolverMultistep",
      num_outputs: 1,
      guidance_scale: 7.5,
      prompt_strength: 0.8,
      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 daanelson/sd-21-fp16 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "daanelson/sd-21-fp16:77ac4b275220676416d58e3fae95ddba590d9b9289222ca2be992a399a955a90",
    input={
        "width": 768,
        "height": 768,
        "prompt": "a photo of an astronaut riding a horse on mars",
        "scheduler": "DPMSolverMultistep",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "prompt_strength": 0.8,
        "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 daanelson/sd-21-fp16 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": "77ac4b275220676416d58e3fae95ddba590d9b9289222ca2be992a399a955a90",
    "input": {
      "width": 768,
      "height": 768,
      "prompt": "a photo of an astronaut riding a horse on mars",
      "scheduler": "DPMSolverMultistep",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "prompt_strength": 0.8,
      "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.

Run time and cost

This model costs approximately $0.10 to run on Replicate, or 10 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 8 minutes.

Readme

This model doesn't have a readme.