Default: ""
Default: 1
Default: 0.15
Default: 92
Default: 20
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
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 impetusdesign/sxn-trd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "impetusdesign/sxn-trd:e1663b7ef15439c40a53b3709745219f7acfd33364a025f04e70e646f356aa45", { input: { seed: 92, image: "https://replicate.delivery/pbxt/MYTyYKwXa8uARHYGYpDv1Kxmea1La0Xoiog5gQ22eaE4GCM2/0.png", prompt: "", padding: 0.15, num_inference_steps: 20, num_images_per_prompt: 1 } } ); // 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
import replicate
output = replicate.run( "impetusdesign/sxn-trd:e1663b7ef15439c40a53b3709745219f7acfd33364a025f04e70e646f356aa45", input={ "seed": 92, "image": "https://replicate.delivery/pbxt/MYTyYKwXa8uARHYGYpDv1Kxmea1La0Xoiog5gQ22eaE4GCM2/0.png", "prompt": "", "padding": 0.15, "num_inference_steps": 20, "num_images_per_prompt": 1 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "impetusdesign/sxn-trd:e1663b7ef15439c40a53b3709745219f7acfd33364a025f04e70e646f356aa45", "input": { "seed": 92, "image": "https://replicate.delivery/pbxt/MYTyYKwXa8uARHYGYpDv1Kxmea1La0Xoiog5gQ22eaE4GCM2/0.png", "prompt": "", "padding": 0.15, "num_inference_steps": 20, "num_images_per_prompt": 1 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{ "completed_at": "2025-02-24T13:56:13.646235Z", "created_at": "2025-02-24T13:53:13.022000Z", "data_removed": false, "error": null, "id": "1vggk9ds7srj60cn70xvkb987m", "input": { "seed": 92, "image": "https://replicate.delivery/pbxt/MYTyYKwXa8uARHYGYpDv1Kxmea1La0Xoiog5gQ22eaE4GCM2/0.png", "prompt": "", "padding": 0.15, "num_inference_steps": 20, "num_images_per_prompt": 1 }, "logs": "0%| | 0/19 [00:00<?, ?it/s]\n 5%|▌ | 1/19 [00:00<00:04, 4.00it/s]\n 16%|█▌ | 3/19 [00:00<00:02, 7.89it/s]\n 21%|██ | 4/19 [00:00<00:01, 8.38it/s]\n 26%|██▋ | 5/19 [00:00<00:01, 8.74it/s]\n 32%|███▏ | 6/19 [00:00<00:01, 9.00it/s]\n 37%|███▋ | 7/19 [00:00<00:01, 9.16it/s]\n 42%|████▏ | 8/19 [00:00<00:01, 9.28it/s]\n 47%|████▋ | 9/19 [00:01<00:01, 9.37it/s]\n 53%|█████▎ | 10/19 [00:01<00:00, 9.43it/s]\n 58%|█████▊ | 11/19 [00:01<00:00, 9.47it/s]\n 63%|██████▎ | 12/19 [00:01<00:00, 9.51it/s]\n 68%|██████▊ | 13/19 [00:01<00:00, 9.54it/s]\n 74%|███████▎ | 14/19 [00:01<00:00, 9.56it/s]\n 79%|███████▉ | 15/19 [00:01<00:00, 9.55it/s]\n 84%|████████▍ | 16/19 [00:01<00:00, 9.54it/s]\n 89%|████████▉ | 17/19 [00:01<00:00, 9.53it/s]\n 95%|█████████▍| 18/19 [00:01<00:00, 9.54it/s]\n100%|██████████| 19/19 [00:02<00:00, 9.56it/s]\n100%|██████████| 19/19 [00:02<00:00, 9.09it/s]", "metrics": { "predict_time": 3.945524672, "total_time": 180.624235 }, "output": [ "https://replicate.delivery/yhqm/6IroTfL1kvW0aqOwVVDsegvq4D5YFvdKlBs1qmVxAtq9xiSUA/output_0.png" ], "started_at": "2025-02-24T13:56:09.700710Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-anp5vbaudbu7o7swp5ev2kg7e4ku6pn7pfzfrekhavfbw3stcbfq", "get": "https://api.replicate.com/v1/predictions/1vggk9ds7srj60cn70xvkb987m", "cancel": "https://api.replicate.com/v1/predictions/1vggk9ds7srj60cn70xvkb987m/cancel" }, "version": "e1663b7ef15439c40a53b3709745219f7acfd33364a025f04e70e646f356aa45" }
0%| | 0/19 [00:00<?, ?it/s] 5%|▌ | 1/19 [00:00<00:04, 4.00it/s] 16%|█▌ | 3/19 [00:00<00:02, 7.89it/s] 21%|██ | 4/19 [00:00<00:01, 8.38it/s] 26%|██▋ | 5/19 [00:00<00:01, 8.74it/s] 32%|███▏ | 6/19 [00:00<00:01, 9.00it/s] 37%|███▋ | 7/19 [00:00<00:01, 9.16it/s] 42%|████▏ | 8/19 [00:00<00:01, 9.28it/s] 47%|████▋ | 9/19 [00:01<00:01, 9.37it/s] 53%|█████▎ | 10/19 [00:01<00:00, 9.43it/s] 58%|█████▊ | 11/19 [00:01<00:00, 9.47it/s] 63%|██████▎ | 12/19 [00:01<00:00, 9.51it/s] 68%|██████▊ | 13/19 [00:01<00:00, 9.54it/s] 74%|███████▎ | 14/19 [00:01<00:00, 9.56it/s] 79%|███████▉ | 15/19 [00:01<00:00, 9.55it/s] 84%|████████▍ | 16/19 [00:01<00:00, 9.54it/s] 89%|████████▉ | 17/19 [00:01<00:00, 9.53it/s] 95%|█████████▍| 18/19 [00:01<00:00, 9.54it/s] 100%|██████████| 19/19 [00:02<00:00, 9.56it/s] 100%|██████████| 19/19 [00:02<00:00, 9.09it/s]
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This model runs on Nvidia A100 (80GB) GPU hardware. We don't yet have enough runs of this model to provide performance information.
This model doesn't have a readme.
This model is cold. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
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