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cjwbw /sd-textual-inversion-ugly-sonic:57d8c937
Input
Run this model in Node.js with one line of code:
npm install replicateREPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run cjwbw/sd-textual-inversion-ugly-sonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"cjwbw/sd-textual-inversion-ugly-sonic:57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483",
{
input: {
prompt: "<ugly-sonic> sitting and eating a ((chili dog)), stock photo",
num_outputs: 1,
guidance_scale: 7.5,
num_inference_steps: 50
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateREPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
import replicateRun cjwbw/sd-textual-inversion-ugly-sonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"cjwbw/sd-textual-inversion-ugly-sonic:57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483",
input={
"prompt": "<ugly-sonic> sitting and eating a ((chili dog)), stock photo",
"num_outputs": 1,
"guidance_scale": 7.5,
"num_inference_steps": 50
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run cjwbw/sd-textual-inversion-ugly-sonic 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": "57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483",
"input": {
"prompt": "<ugly-sonic> sitting and eating a ((chili dog)), stock photo",
"num_outputs": 1,
"guidance_scale": 7.5,
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
brew install cogIf 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/chenxwh/sd-textual-inversion-ugly-sonic@sha256:57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483 \
-i 'prompt="<ugly-sonic> sitting and eating a ((chili dog)), stock photo"' \
-i 'num_outputs=1' \
-i 'guidance_scale=7.5' \
-i 'num_inference_steps=50'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/chenxwh/sd-textual-inversion-ugly-sonic@sha256:57d8c937dead2f8437b8c93e586fa8dec20841dfdfc63ff5b4719ee8b867d483curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "prompt": "<ugly-sonic> sitting and eating a ((chili dog)), stock photo", "num_outputs": 1, "guidance_scale": 7.5, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
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Output
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