chenxwh/meissonic:92c16966 – Run with an API on Replicate

Version

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chenxwh /meissonic:92c16966

Input

prompt

string

Shift + Return to add a new line

a photo of an astronaut riding a horse on marsa photo of an astronaut riding a horse on mars

Input prompt

Default: "a photo of an astronaut riding a horse on mars"

negative_prompt

string

Shift + Return to add a new line

worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying markworst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark

Specify things to not see in the output

Default: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark"

num_inference_steps

integer

(minimum: 1, maximum: 100)

Number of denoising steps

Default: 64

guidance_scale

number

(minimum: 0, maximum: 20)

Scale for classifier-free guidance

Default: 9

seed

integer

Random seed. Leave blank to randomize the seed

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

npx create-replicate --model=chenxwh/meissonic

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

const output = await replicate.run(
  "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21",
  {
    input: {
      prompt: "a photo of an astronaut riding a horse on mars",
      guidance_scale: 9,
      negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark",
      num_inference_steps: 64
    }
  }
);
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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21",
    input={
        "prompt": "a photo of an astronaut riding a horse on mars",
        "guidance_scale": 9,
        "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark",
        "num_inference_steps": 64
    }
)
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 chenxwh/meissonic 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": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21",
    "input": {
      "prompt": "a photo of an astronaut riding a horse on mars",
      "guidance_scale": 9,
      "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark",
      "num_inference_steps": 64
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run chenxwh/meissonic using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/chenxwh/meissonic@sha256:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21 \
  -i 'prompt="a photo of an astronaut riding a horse on mars"' \
  -i 'guidance_scale=9' \
  -i 'negative_prompt="worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark"' \
  -i 'num_inference_steps=64'

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

Pull and run chenxwh/meissonic using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/chenxwh/meissonic@sha256:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "prompt": "a photo of an astronaut riding a horse on mars",
      "guidance_scale": 9,
      "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark",
      "num_inference_steps": 64
    }
  }' \
  http://localhost:5000/predictions

Output

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