You're looking at a specific version of this model. Jump to the model overview.
jagilley /stable-diffusion-upscaler:4d0aeee7
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variableexport 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 jagilley/stable-diffusion-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"jagilley/stable-diffusion-upscaler:4d0aeee7387b1170b0f6f42bdf14c7d9d8e00a15430d95446ad7426dc61fc3d8",
{
input: {
eta: 1,
scale: 1.5,
steps: 10,
prompt: "",
decoder: "finetuned_840k",
sampler: "k_dpm_adaptive",
tol_scale: 0.25,
batch_size: 1,
num_samples: 1,
guidance_scale: 1,
noise_aug_type: "gaussian",
noise_aug_level: 0
}
}
);
console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run jagilley/stable-diffusion-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"jagilley/stable-diffusion-upscaler:4d0aeee7387b1170b0f6f42bdf14c7d9d8e00a15430d95446ad7426dc61fc3d8",
input={
"eta": 1,
"scale": 1.5,
"steps": 10,
"prompt": "",
"decoder": "finetuned_840k",
"sampler": "k_dpm_adaptive",
"tol_scale": 0.25,
"batch_size": 1,
"num_samples": 1,
"guidance_scale": 1,
"noise_aug_type": "gaussian",
"noise_aug_level": 0
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run jagilley/stable-diffusion-upscaler 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": "4d0aeee7387b1170b0f6f42bdf14c7d9d8e00a15430d95446ad7426dc61fc3d8",
"input": {
"eta": 1,
"scale": 1.5,
"steps": 10,
"prompt": "",
"decoder": "finetuned_840k",
"sampler": "k_dpm_adaptive",
"tol_scale": 0.25,
"batch_size": 1,
"num_samples": 1,
"guidance_scale": 1,
"noise_aug_type": "gaussian",
"noise_aug_level": 0
}
}' \
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.
Pull and run jagilley/stable-diffusion-upscaler using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/jagilley/stable-diffusion-upscaler@sha256:4d0aeee7387b1170b0f6f42bdf14c7d9d8e00a15430d95446ad7426dc61fc3d8 \
-i 'eta=1' \
-i 'scale=1.5' \
-i 'steps=10' \
-i 'prompt=""' \
-i 'decoder="finetuned_840k"' \
-i 'sampler="k_dpm_adaptive"' \
-i 'tol_scale=0.25' \
-i 'batch_size=1' \
-i 'num_samples=1' \
-i 'guidance_scale=1' \
-i 'noise_aug_type="gaussian"' \
-i 'noise_aug_level=0'
To learn more, take a look at the Cog documentation.
Pull and run jagilley/stable-diffusion-upscaler 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/jagilley/stable-diffusion-upscaler@sha256:4d0aeee7387b1170b0f6f42bdf14c7d9d8e00a15430d95446ad7426dc61fc3d8
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "eta": 1, "scale": 1.5, "steps": 10, "prompt": "", "decoder": "finetuned_840k", "sampler": "k_dpm_adaptive", "tol_scale": 0.25, "batch_size": 1, "num_samples": 1, "guidance_scale": 1, "noise_aug_type": "gaussian", "noise_aug_level": 0 } }' \ http://localhost:5000/predictions
Add a payment method to run this model.
Each run costs approximately $0.077. Alternatively, try out our featured models for free.
By signing in, you agree to our
terms of service and privacy policy
Output
No output yet! Press "Submit" to start a prediction.