You're looking at a specific version of this model. Jump to the model overview.
grandlineai /instant-id-photorealistic:03914a0c
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 grandlineai/instant-id-photorealistic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"grandlineai/instant-id-photorealistic:03914a0c3326bf44383d0cd84b06822618af879229ce5d1d53bef38d93b68279",
{
input: {
width: 640,
height: 640,
prompt: "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality",
guidance_scale: 5,
negative_prompt: "",
ip_adapter_scale: 0.8,
num_inference_steps: 30,
controlnet_conditioning_scale: 0.8
}
}
);
// 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 grandlineai/instant-id-photorealistic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"grandlineai/instant-id-photorealistic:03914a0c3326bf44383d0cd84b06822618af879229ce5d1d53bef38d93b68279",
input={
"width": 640,
"height": 640,
"prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality",
"guidance_scale": 5,
"negative_prompt": "",
"ip_adapter_scale": 0.8,
"num_inference_steps": 30,
"controlnet_conditioning_scale": 0.8
}
)
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 grandlineai/instant-id-photorealistic 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": "03914a0c3326bf44383d0cd84b06822618af879229ce5d1d53bef38d93b68279",
"input": {
"width": 640,
"height": 640,
"prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality",
"guidance_scale": 5,
"negative_prompt": "",
"ip_adapter_scale": 0.8,
"num_inference_steps": 30,
"controlnet_conditioning_scale": 0.8
}
}' \
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/grandlineai/instant-id-photorealistic@sha256:03914a0c3326bf44383d0cd84b06822618af879229ce5d1d53bef38d93b68279 \
-i 'width=640' \
-i 'height=640' \
-i 'prompt="analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality"' \
-i 'guidance_scale=5' \
-i 'negative_prompt=""' \
-i 'ip_adapter_scale=0.8' \
-i 'num_inference_steps=30' \
-i 'controlnet_conditioning_scale=0.8'
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/grandlineai/instant-id-photorealistic@sha256:03914a0c3326bf44383d0cd84b06822618af879229ce5d1d53bef38d93b68279
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 640, "height": 640, "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "guidance_scale": 5, "negative_prompt": "", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Each run costs approximately $0.057. 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.