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ai-forever /kandinsky-2:3c6374e7
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=ai-forever/kandinsky-2
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run ai-forever/kandinsky-2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"ai-forever/kandinsky-2:3c6374e7a9a17e01afe306a5218cc67de55b19ea536466d6ea2602cfecea40a9",
{
input: {
width: 512,
height: 512,
prompt: "red cat, 4k photo",
scheduler: "p_sampler",
batch_size: 1,
prior_steps: "5",
output_format: "webp",
guidance_scale: 4,
output_quality: 80,
prior_cf_scale: 4,
num_inference_steps: 100
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun ai-forever/kandinsky-2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"ai-forever/kandinsky-2:3c6374e7a9a17e01afe306a5218cc67de55b19ea536466d6ea2602cfecea40a9",
input={
"width": 512,
"height": 512,
"prompt": "red cat, 4k photo",
"scheduler": "p_sampler",
"batch_size": 1,
"prior_steps": "5",
"output_format": "webp",
"guidance_scale": 4,
"output_quality": 80,
"prior_cf_scale": 4,
"num_inference_steps": 100
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run ai-forever/kandinsky-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": "3c6374e7a9a17e01afe306a5218cc67de55b19ea536466d6ea2602cfecea40a9",
"input": {
"width": 512,
"height": 512,
"prompt": "red cat, 4k photo",
"scheduler": "p_sampler",
"batch_size": 1,
"prior_steps": "5",
"output_format": "webp",
"guidance_scale": 4,
"output_quality": 80,
"prior_cf_scale": 4,
"num_inference_steps": 100
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
Sign in with GitHub
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terms of service and privacy policy
Output
{
"completed_at": "2023-04-05T14:18:17.379573Z",
"created_at": "2023-04-05T14:17:05.824020Z",
"data_removed": false,
"error": null,
"id": "wixq75uo65glnjcdgrqtngdz4q",
"input": {
"prompt": "red cat, 4k photo",
"scheduler": "p_sampler",
"prior_steps": "5",
"guidance_scale": 4,
"prior_cf_scale": 4,
"num_inference_steps": 100
},
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"metrics": {
"predict_time": 71.261476,
"total_time": 71.555553
},
"output": "https://replicate.delivery/pbxt/NsOpfQRos43e40IzSq4SY7NTtxGodmSWo1m74K17SVpoUzuQA/out.png",
"started_at": "2023-04-05T14:17:06.118097Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/wixq75uo65glnjcdgrqtngdz4q",
"cancel": "https://api.replicate.com/v1/predictions/wixq75uo65glnjcdgrqtngdz4q/cancel"
},
"version": "9c0bf7d5cf2ed934c5921faf61882657c03c4def9d9cb88330c15bd795edb098"
}Generated in
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100%|██████████| 100/100 [01:04<00:00, 1.55it/s]This example was created by a different version, ai-forever/kandinsky-2:9c0bf7d5.