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charlesmccarthy /animagine-xl:db29f76d
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_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 charlesmccarthy/animagine-xl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"charlesmccarthy/animagine-xl:db29f76d40ecf86335295ca5b24ed95e6b1eca4e29239c47cfefa68f408cbf5e",
{
input: {
width: 1024,
height: 1024,
prompt: "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed",
scheduler: "KarrasDPM",
num_outputs: 1,
guidance_scale: 7.5,
apply_watermark: true,
negative_prompt: "worst quality, low quality",
prompt_strength: 0.8,
num_inference_steps: 60
}
}
);
// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run charlesmccarthy/animagine-xl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"charlesmccarthy/animagine-xl:db29f76d40ecf86335295ca5b24ed95e6b1eca4e29239c47cfefa68f408cbf5e",
input={
"width": 1024,
"height": 1024,
"prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed",
"scheduler": "KarrasDPM",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": True,
"negative_prompt": "worst quality, low quality",
"prompt_strength": 0.8,
"num_inference_steps": 60
}
)
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 charlesmccarthy/animagine-xl 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": "db29f76d40ecf86335295ca5b24ed95e6b1eca4e29239c47cfefa68f408cbf5e",
"input": {
"width": 1024,
"height": 1024,
"prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed",
"scheduler": "KarrasDPM",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"negative_prompt": "worst quality, low quality",
"prompt_strength": 0.8,
"num_inference_steps": 60
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
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/charlesmccarthy/animagine-xl@sha256:db29f76d40ecf86335295ca5b24ed95e6b1eca4e29239c47cfefa68f408cbf5e \
-i 'width=1024' \
-i 'height=1024' \
-i 'prompt="black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed"' \
-i 'scheduler="KarrasDPM"' \
-i 'num_outputs=1' \
-i 'guidance_scale=7.5' \
-i 'apply_watermark=true' \
-i 'negative_prompt="worst quality, low quality"' \
-i 'prompt_strength=0.8' \
-i 'num_inference_steps=60'
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/charlesmccarthy/animagine-xl@sha256:db29f76d40ecf86335295ca5b24ed95e6b1eca4e29239c47cfefa68f408cbf5e
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed", "scheduler": "KarrasDPM", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "worst quality, low quality", "prompt_strength": 0.8, "num_inference_steps": 60 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
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Output
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