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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";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run camenduru/magictime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"camenduru/magictime:91e4bb80b45832b5bafdbc10d94fd1d364d0d6ad80f5b1498fcb25d217cb3a9c",
{
input: {
seed: "1496541313",
width: 512,
height: 512,
prompt: "Time-lapse of dough balls transforming into bread rolls: Begins with smooth, proofed dough, gradually expands in early baking, becomes taut and voluminous, and finally browns and fully expands to signal the baking's completion.",
dreambooth: "ToonYou_beta6.safetensors",
negative_prompt: "worst quality, low quality, letterboxed"
}
}
);
// 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 camenduru/magictime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"camenduru/magictime:91e4bb80b45832b5bafdbc10d94fd1d364d0d6ad80f5b1498fcb25d217cb3a9c",
input={
"seed": "1496541313",
"width": 512,
"height": 512,
"prompt": "Time-lapse of dough balls transforming into bread rolls: Begins with smooth, proofed dough, gradually expands in early baking, becomes taut and voluminous, and finally browns and fully expands to signal the baking's completion.",
"dreambooth": "ToonYou_beta6.safetensors",
"negative_prompt": "worst quality, low quality, letterboxed"
}
)
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 camenduru/magictime 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": "camenduru/magictime:91e4bb80b45832b5bafdbc10d94fd1d364d0d6ad80f5b1498fcb25d217cb3a9c",
"input": {
"seed": "1496541313",
"width": 512,
"height": 512,
"prompt": "Time-lapse of dough balls transforming into bread rolls: Begins with smooth, proofed dough, gradually expands in early baking, becomes taut and voluminous, and finally browns and fully expands to signal the baking\'s completion.",
"dreambooth": "ToonYou_beta6.safetensors",
"negative_prompt": "worst quality, low quality, letterboxed"
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
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Output
{
"completed_at": "2024-04-13T12:28:25.863163Z",
"created_at": "2024-04-13T12:26:28.682000Z",
"data_removed": false,
"error": null,
"id": "ebe86tk3s9rgg0cetxpbz042f4",
"input": {
"seed": "1496541313",
"width": 512,
"height": 512,
"prompt": "Time-lapse of dough balls transforming into bread rolls: Begins with smooth, proofed dough, gradually expands in early baking, becomes taut and voluminous, and finally browns and fully expands to signal the baking's completion.",
"dreambooth": "ToonYou_beta6.safetensors",
"negative_prompt": "worst quality, low quality, letterboxed"
},
"logs": "### seed: 1496541313\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:01<00:41, 1.73s/it]\n 8%|▊ | 2/25 [00:03<00:39, 1.73s/it]\n 12%|█▏ | 3/25 [00:05<00:38, 1.73s/it]\n 16%|█▌ | 4/25 [00:06<00:36, 1.73s/it]\n 20%|██ | 5/25 [00:08<00:34, 1.73s/it]\n 24%|██▍ | 6/25 [00:10<00:32, 1.73s/it]\n 28%|██▊ | 7/25 [00:12<00:31, 1.74s/it]\n 32%|███▏ | 8/25 [00:13<00:29, 1.74s/it]\n 36%|███▌ | 9/25 [00:15<00:27, 1.74s/it]\n 40%|████ | 10/25 [00:17<00:26, 1.74s/it]\n 44%|████▍ | 11/25 [00:19<00:24, 1.74s/it]\n 48%|████▊ | 12/25 [00:20<00:22, 1.74s/it]\n 52%|█████▏ | 13/25 [00:22<00:20, 1.74s/it]\n 56%|█████▌ | 14/25 [00:24<00:19, 1.74s/it]\n 60%|██████ | 15/25 [00:26<00:17, 1.74s/it]\n 64%|██████▍ | 16/25 [00:27<00:15, 1.74s/it]\n 68%|██████▊ | 17/25 [00:29<00:13, 1.74s/it]\n 72%|███████▏ | 18/25 [00:31<00:12, 1.74s/it]\n 76%|███████▌ | 19/25 [00:32<00:10, 1.74s/it]\n 80%|████████ | 20/25 [00:34<00:08, 1.74s/it]\n 84%|████████▍ | 21/25 [00:36<00:06, 1.74s/it]\n 88%|████████▊ | 22/25 [00:38<00:05, 1.74s/it]\n 92%|█████████▏| 23/25 [00:39<00:03, 1.74s/it]\n 96%|█████████▌| 24/25 [00:41<00:01, 1.74s/it]\n100%|██████████| 25/25 [00:43<00:00, 1.74s/it]\n100%|██████████| 25/25 [00:43<00:00, 1.74s/it]\n 0%| | 0/16 [00:00<?, ?it/s]\n 31%|███▏ | 5/16 [00:00<00:00, 48.45it/s]\n 62%|██████▎ | 10/16 [00:00<00:00, 25.48it/s]\n 88%|████████▊ | 14/16 [00:00<00:00, 22.46it/s]\n100%|██████████| 16/16 [00:00<00:00, 23.58it/s]",
"metrics": {
"predict_time": 47.958111,
"total_time": 117.181163
},
"output": "https://replicate.delivery/pbxt/cvZctpvbfhRDRyE4csqXeH2yc47BGIzThefAAeGlSFeBasgqE/sample.mp4",
"started_at": "2024-04-13T12:27:37.905052Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/ebe86tk3s9rgg0cetxpbz042f4",
"cancel": "https://api.replicate.com/v1/predictions/ebe86tk3s9rgg0cetxpbz042f4/cancel"
},
"version": "91e4bb80b45832b5bafdbc10d94fd1d364d0d6ad80f5b1498fcb25d217cb3a9c"
}
### seed: 1496541313
0%| | 0/25 [00:00<?, ?it/s]
4%|▍ | 1/25 [00:01<00:41, 1.73s/it]
8%|▊ | 2/25 [00:03<00:39, 1.73s/it]
12%|█▏ | 3/25 [00:05<00:38, 1.73s/it]
16%|█▌ | 4/25 [00:06<00:36, 1.73s/it]
20%|██ | 5/25 [00:08<00:34, 1.73s/it]
24%|██▍ | 6/25 [00:10<00:32, 1.73s/it]
28%|██▊ | 7/25 [00:12<00:31, 1.74s/it]
32%|███▏ | 8/25 [00:13<00:29, 1.74s/it]
36%|███▌ | 9/25 [00:15<00:27, 1.74s/it]
40%|████ | 10/25 [00:17<00:26, 1.74s/it]
44%|████▍ | 11/25 [00:19<00:24, 1.74s/it]
48%|████▊ | 12/25 [00:20<00:22, 1.74s/it]
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56%|█████▌ | 14/25 [00:24<00:19, 1.74s/it]
60%|██████ | 15/25 [00:26<00:17, 1.74s/it]
64%|██████▍ | 16/25 [00:27<00:15, 1.74s/it]
68%|██████▊ | 17/25 [00:29<00:13, 1.74s/it]
72%|███████▏ | 18/25 [00:31<00:12, 1.74s/it]
76%|███████▌ | 19/25 [00:32<00:10, 1.74s/it]
80%|████████ | 20/25 [00:34<00:08, 1.74s/it]
84%|████████▍ | 21/25 [00:36<00:06, 1.74s/it]
88%|████████▊ | 22/25 [00:38<00:05, 1.74s/it]
92%|█████████▏| 23/25 [00:39<00:03, 1.74s/it]
96%|█████████▌| 24/25 [00:41<00:01, 1.74s/it]
100%|██████████| 25/25 [00:43<00:00, 1.74s/it]
100%|██████████| 25/25 [00:43<00:00, 1.74s/it]
0%| | 0/16 [00:00<?, ?it/s]
31%|███▏ | 5/16 [00:00<00:00, 48.45it/s]
62%|██████▎ | 10/16 [00:00<00:00, 25.48it/s]
88%|████████▊ | 14/16 [00:00<00:00, 22.46it/s]
100%|██████████| 16/16 [00:00<00:00, 23.58it/s]