ecg/tobogganstyle
tobogganstyle
Prediction
ecg/tobogganstyle:e5c5728bIDrwe80yxzsnrma0cqakmad0ewtgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Children playing in a colorful toboggan water park, sun flare, tobogganstyle, summer, sunlight,
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 4
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Children playing in a colorful toboggan water park, sun flare, tobogganstyle, summer, sunlight, ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run ecg/tobogganstyle using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ecg/tobogganstyle:e5c5728b927d4991d110027cfc23d89129ebbf3952602e1544807dbc732faaa2", { input: { model: "dev", prompt: "Children playing in a colorful toboggan water park, sun flare, tobogganstyle, summer, sunlight, ", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 4, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun ecg/tobogganstyle using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ecg/tobogganstyle:e5c5728b927d4991d110027cfc23d89129ebbf3952602e1544807dbc732faaa2", input={ "model": "dev", "prompt": "Children playing in a colorful toboggan water park, sun flare, tobogganstyle, summer, sunlight, ", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run ecg/tobogganstyle 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": "ecg/tobogganstyle:e5c5728b927d4991d110027cfc23d89129ebbf3952602e1544807dbc732faaa2", "input": { "model": "dev", "prompt": "Children playing in a colorful toboggan water park, sun flare, tobogganstyle, summer, sunlight, ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-06-09T13:37:47.329110Z", "created_at": "2025-06-09T13:37:09.069000Z", "data_removed": false, "error": null, "id": "rwe80yxzsnrma0cqakmad0ewtg", "input": { "model": "dev", "prompt": "Children playing in a colorful toboggan water park, sun flare, tobogganstyle, summer, sunlight, ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=27069111767040\nDownloading weights\n2025-06-09T13:37:18Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmplix7_x_y/weights url=https://replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar\n2025-06-09T13:37:18Z | INFO | [ Cache Service ] enabled=true scheme=http target=hermes.services.svc.cluster.local\n2025-06-09T13:37:18Z | INFO | [ Cache URL Rewrite ] enabled=true target_url=http://hermes.services.svc.cluster.local/replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar url=https://replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar\n2025-06-09T13:37:18Z | INFO | [ Redirect ] redirect_url=http://r8-east4-loras-ric1.cwlota.com/84b9a5f8e80b690e63938a6e5bff4920da6168d51fec60de1827e0dbf63042ef?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Checksum-Mode=ENABLED&X-Amz-Credential=CWNZUVKLDHXVHEZN%2F20250609%2FUS-EAST-04A%2Fs3%2Faws4_request&X-Amz-Date=20250609T133718Z&X-Amz-Expires=600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=72d08a7bcb7749dfa10bb57fa52783e35987bdb0ce6350a6448d227e0b3253eb url=http://hermes.services.svc.cluster.local/replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar\n2025-06-09T13:37:18Z | INFO | [ Complete ] dest=/tmp/tmplix7_x_y/weights size=\"172 MB\" total_elapsed=0.293s url=https://replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar\nDownloaded weights in 0.35s\nLoaded LoRAs in 0.87s\nUsing seed: 43358\nPrompt: Children playing in a colorful toboggan water park, sun flare, tobogganstyle, summer, sunlight,\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:26, 1.03it/s]\n 7%|▋ | 2/28 [00:01<00:22, 1.17it/s]\n 11%|█ | 3/28 [00:02<00:22, 1.10it/s]\n 14%|█▍ | 4/28 [00:03<00:22, 1.07it/s]\n 18%|█▊ | 5/28 [00:04<00:21, 1.05it/s]\n 21%|██▏ | 6/28 [00:05<00:21, 1.04it/s]\n 25%|██▌ | 7/28 [00:06<00:20, 1.04it/s]\n 29%|██▊ | 8/28 [00:07<00:19, 1.03it/s]\n 32%|███▏ | 9/28 [00:08<00:18, 1.03it/s]\n 36%|███▌ | 10/28 [00:09<00:17, 1.03it/s]\n 39%|███▉ | 11/28 [00:10<00:16, 1.03it/s]\n 43%|████▎ | 12/28 [00:11<00:15, 1.03it/s]\n 46%|████▋ | 13/28 [00:12<00:14, 1.03it/s]\n 50%|█████ | 14/28 [00:13<00:13, 1.03it/s]\n 54%|█████▎ | 15/28 [00:14<00:12, 1.03it/s]\n 57%|█████▋ | 16/28 [00:15<00:11, 1.03it/s]\n 61%|██████ | 17/28 [00:16<00:10, 1.03it/s]\n 64%|██████▍ | 18/28 [00:17<00:09, 1.03it/s]\n 68%|██████▊ | 19/28 [00:18<00:08, 1.03it/s]\n 71%|███████▏ | 20/28 [00:19<00:07, 1.03it/s]\n 75%|███████▌ | 21/28 [00:20<00:06, 1.03it/s]\n 79%|███████▊ | 22/28 [00:21<00:05, 1.03it/s]\n 82%|████████▏ | 23/28 [00:22<00:04, 1.03it/s]\n 86%|████████▌ | 24/28 [00:23<00:03, 1.03it/s]\n 89%|████████▉ | 25/28 [00:24<00:02, 1.03it/s]\n 93%|█████████▎| 26/28 [00:25<00:01, 1.03it/s]\n 96%|█████████▋| 27/28 [00:26<00:00, 1.03it/s]\n100%|██████████| 28/28 [00:27<00:00, 1.03it/s]\n100%|██████████| 28/28 [00:27<00:00, 1.03it/s]\nTotal safe images: 4 out of 4", "metrics": { "predict_time": 28.936680517, "total_time": 38.26011 }, "output": [ "https://replicate.delivery/xezq/LeHenXvzpUsh0kkxLerxiXuDZ0y4oLxfMzMSzUmUnVed1KpmC/out-0.webp", "https://replicate.delivery/xezq/7Upcn5pq9M7xFBw9MdHYTlU1zjUDFJaFVYyEwD9dz85qVSNF/out-1.webp", "https://replicate.delivery/xezq/1holxcGMJUrCORCnD6ApzGNf5pHpouqzH8KNX6cviqsVrkaKA/out-2.webp", "https://replicate.delivery/xezq/PGaUIavof6yWFyisf0TmfydzNShrnhbuyIUjdosibx1WtSqpA/out-3.webp" ], "started_at": "2025-06-09T13:37:18.392430Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-znehxymhmrkzxiofnuykjxlqyvumwdyhmxofy6wiud5vdmjcfoka", "get": "https://api.replicate.com/v1/predictions/rwe80yxzsnrma0cqakmad0ewtg", "cancel": "https://api.replicate.com/v1/predictions/rwe80yxzsnrma0cqakmad0ewtg/cancel" }, "version": "e5c5728b927d4991d110027cfc23d89129ebbf3952602e1544807dbc732faaa2" }Generated infree=27069111767040 Downloading weights 2025-06-09T13:37:18Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmplix7_x_y/weights url=https://replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar 2025-06-09T13:37:18Z | INFO | [ Cache Service ] enabled=true scheme=http target=hermes.services.svc.cluster.local 2025-06-09T13:37:18Z | INFO | [ Cache URL Rewrite ] enabled=true target_url=http://hermes.services.svc.cluster.local/replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar url=https://replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar 2025-06-09T13:37:18Z | INFO | [ Redirect ] redirect_url=http://r8-east4-loras-ric1.cwlota.com/84b9a5f8e80b690e63938a6e5bff4920da6168d51fec60de1827e0dbf63042ef?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Checksum-Mode=ENABLED&X-Amz-Credential=CWNZUVKLDHXVHEZN%2F20250609%2FUS-EAST-04A%2Fs3%2Faws4_request&X-Amz-Date=20250609T133718Z&X-Amz-Expires=600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=72d08a7bcb7749dfa10bb57fa52783e35987bdb0ce6350a6448d227e0b3253eb url=http://hermes.services.svc.cluster.local/replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar 2025-06-09T13:37:18Z | INFO | [ Complete ] dest=/tmp/tmplix7_x_y/weights size="172 MB" total_elapsed=0.293s url=https://replicate.delivery/xezq/rLH2IyynDf39JCSfovu0iMxXTZoOF0R3wRlTIZyryn9yDJ1UA/flux-lora.tar Downloaded weights in 0.35s Loaded LoRAs in 0.87s Using seed: 43358 Prompt: Children playing in a colorful toboggan water park, sun flare, tobogganstyle, summer, sunlight, [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:26, 1.03it/s] 7%|▋ | 2/28 [00:01<00:22, 1.17it/s] 11%|█ | 3/28 [00:02<00:22, 1.10it/s] 14%|█▍ | 4/28 [00:03<00:22, 1.07it/s] 18%|█▊ | 5/28 [00:04<00:21, 1.05it/s] 21%|██▏ | 6/28 [00:05<00:21, 1.04it/s] 25%|██▌ | 7/28 [00:06<00:20, 1.04it/s] 29%|██▊ | 8/28 [00:07<00:19, 1.03it/s] 32%|███▏ | 9/28 [00:08<00:18, 1.03it/s] 36%|███▌ | 10/28 [00:09<00:17, 1.03it/s] 39%|███▉ | 11/28 [00:10<00:16, 1.03it/s] 43%|████▎ | 12/28 [00:11<00:15, 1.03it/s] 46%|████▋ | 13/28 [00:12<00:14, 1.03it/s] 50%|█████ | 14/28 [00:13<00:13, 1.03it/s] 54%|█████▎ | 15/28 [00:14<00:12, 1.03it/s] 57%|█████▋ | 16/28 [00:15<00:11, 1.03it/s] 61%|██████ | 17/28 [00:16<00:10, 1.03it/s] 64%|██████▍ | 18/28 [00:17<00:09, 1.03it/s] 68%|██████▊ | 19/28 [00:18<00:08, 1.03it/s] 71%|███████▏ | 20/28 [00:19<00:07, 1.03it/s] 75%|███████▌ | 21/28 [00:20<00:06, 1.03it/s] 79%|███████▊ | 22/28 [00:21<00:05, 1.03it/s] 82%|████████▏ | 23/28 [00:22<00:04, 1.03it/s] 86%|████████▌ | 24/28 [00:23<00:03, 1.03it/s] 89%|████████▉ | 25/28 [00:24<00:02, 1.03it/s] 93%|█████████▎| 26/28 [00:25<00:01, 1.03it/s] 96%|█████████▋| 27/28 [00:26<00:00, 1.03it/s] 100%|██████████| 28/28 [00:27<00:00, 1.03it/s] 100%|██████████| 28/28 [00:27<00:00, 1.03it/s] Total safe images: 4 out of 4
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