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piyushk52 /ad_interpolation_2:1bf7d2a3
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 piyushk52/ad_interpolation_2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"piyushk52/ad_interpolation_2:1bf7d2a322ea2d6f95983fa833f1870db966164dde62e584e15954d5556fd01a",
{
input: {
cfg: 8,
seed: -1,
model: "Counterfeit-V3.0_fp32.safetensors",
sampler: "dpmpp_2m",
motion_module: "mm_sd_v14.ckpt",
sampling_steps: 30,
image_dimension: "512x512",
ending_img_controlnet_weight: 0.8,
ending_image_latent_cn_weights: "0=0.0, 1=0.13, 2=0.24, 3=0.34, 4=0.43, 5=0.50, 6=0.57, 7=0.63, 8=0.68, 9=0.72, 10=1.0, 11=1.0, 12=1.0, 13=1.0, 14=1.0, 15=1.0",
starting_img_controlnet_weight: 0.8,
starting_image_latent_cn_weights: "0=1.0, 1=0.87, 2=0.76, 3=0.66, 4=0.57, 5=0.50, 6=0.43, 7=0.37, 8=0.32, 9=0.28, 10=0.0, 11=0.0, 12=0.0, 13=0.0, 14=0.0, 15=0.0"
}
}
);
// To access the file URL:
console.log(output.url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output);
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 piyushk52/ad_interpolation_2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"piyushk52/ad_interpolation_2:1bf7d2a322ea2d6f95983fa833f1870db966164dde62e584e15954d5556fd01a",
input={
"cfg": 8,
"seed": -1,
"model": "Counterfeit-V3.0_fp32.safetensors",
"sampler": "dpmpp_2m",
"motion_module": "mm_sd_v14.ckpt",
"sampling_steps": 30,
"image_dimension": "512x512",
"ending_img_controlnet_weight": 0.8,
"ending_image_latent_cn_weights": "0=0.0, 1=0.13, 2=0.24, 3=0.34, 4=0.43, 5=0.50, 6=0.57, 7=0.63, 8=0.68, 9=0.72, 10=1.0, 11=1.0, 12=1.0, 13=1.0, 14=1.0, 15=1.0",
"starting_img_controlnet_weight": 0.8,
"starting_image_latent_cn_weights": "0=1.0, 1=0.87, 2=0.76, 3=0.66, 4=0.57, 5=0.50, 6=0.43, 7=0.37, 8=0.32, 9=0.28, 10=0.0, 11=0.0, 12=0.0, 13=0.0, 14=0.0, 15=0.0"
}
)
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 piyushk52/ad_interpolation_2 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": "1bf7d2a322ea2d6f95983fa833f1870db966164dde62e584e15954d5556fd01a",
"input": {
"cfg": 8,
"seed": -1,
"model": "Counterfeit-V3.0_fp32.safetensors",
"sampler": "dpmpp_2m",
"motion_module": "mm_sd_v14.ckpt",
"sampling_steps": 30,
"image_dimension": "512x512",
"ending_img_controlnet_weight": 0.8,
"ending_image_latent_cn_weights": "0=0.0, 1=0.13, 2=0.24, 3=0.34, 4=0.43, 5=0.50, 6=0.57, 7=0.63, 8=0.68, 9=0.72, 10=1.0, 11=1.0, 12=1.0, 13=1.0, 14=1.0, 15=1.0",
"starting_img_controlnet_weight": 0.8,
"starting_image_latent_cn_weights": "0=1.0, 1=0.87, 2=0.76, 3=0.66, 4=0.57, 5=0.50, 6=0.43, 7=0.37, 8=0.32, 9=0.28, 10=0.0, 11=0.0, 12=0.0, 13=0.0, 14=0.0, 15=0.0"
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
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Output
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