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moayedhajiali /elasticdiffusion:bddc0936
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=moayedhajiali/elasticdiffusion
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 moayedhajiali/elasticdiffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"moayedhajiali/elasticdiffusion:bddc09369f9e622518f6d11daff26723a513714e08830ed053660d8ac44ffe88",
{
input: {
seed: 0,
prompt: "An illustration of an astronaut riding a horse",
img_width: 512,
rrg_scale: 0,
img_height: 512,
cosine_scale: 10,
guidance_scale: 10,
view_batch_size: 16,
negative_prompts: "blurry, ugly, poorly drawn, deformed",
resampling_new_p: 0.3,
resampling_steps: 0,
num_inference_steps: 50
}
}
);
// 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.
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 moayedhajiali/elasticdiffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"moayedhajiali/elasticdiffusion:bddc09369f9e622518f6d11daff26723a513714e08830ed053660d8ac44ffe88",
input={
"seed": 0,
"prompt": "An illustration of an astronaut riding a horse",
"img_width": 512,
"rrg_scale": 0,
"img_height": 512,
"cosine_scale": 10,
"guidance_scale": 10,
"view_batch_size": 16,
"negative_prompts": "blurry, ugly, poorly drawn, deformed",
"resampling_new_p": 0.3,
"resampling_steps": 0,
"num_inference_steps": 50
}
)
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 moayedhajiali/elasticdiffusion 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": "bddc09369f9e622518f6d11daff26723a513714e08830ed053660d8ac44ffe88",
"input": {
"seed": 0,
"prompt": "An illustration of an astronaut riding a horse",
"img_width": 512,
"rrg_scale": 0,
"img_height": 512,
"cosine_scale": 10,
"guidance_scale": 10,
"view_batch_size": 16,
"negative_prompts": "blurry, ugly, poorly drawn, deformed",
"resampling_new_p": 0.3,
"resampling_steps": 0,
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
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terms of service and privacy policy
Output
{
"completed_at": "2023-12-28T04:08:59.940491Z",
"created_at": "2023-12-28T04:08:14.157526Z",
"data_removed": false,
"error": null,
"id": "2mog35lbq2xztefdcmgjs7dprq",
"input": {
"seed": 0,
"prompt": "An illustration of an astronaut riding a horse",
"img_width": 512,
"rrg_scale": 0,
"img_height": 512,
"cosine_scale": 10,
"guidance_scale": 10,
"view_batch_size": 16,
"negative_prompts": "blurry, ugly, poorly drawn, deformed",
"resampling_new_p": 0.3,
"resampling_steps": 0,
"num_inference_steps": 50
},
"logs": "0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:44, 1.09it/s]\n 4%|▍ | 2/50 [00:01<00:43, 1.11it/s]\n 6%|▌ | 3/50 [00:02<00:42, 1.12it/s]\n 8%|▊ | 4/50 [00:03<00:41, 1.12it/s]\n 10%|█ | 5/50 [00:04<00:40, 1.12it/s]\n 12%|█▏ | 6/50 [00:05<00:39, 1.12it/s]\n 14%|█▍ | 7/50 [00:06<00:38, 1.12it/s]\n 16%|█▌ | 8/50 [00:07<00:37, 1.12it/s]\n 18%|█▊ | 9/50 [00:08<00:36, 1.12it/s]\n 20%|██ | 10/50 [00:08<00:35, 1.12it/s]\n 22%|██▏ | 11/50 [00:09<00:34, 1.12it/s]\n 24%|██▍ | 12/50 [00:10<00:33, 1.12it/s]\n 26%|██▌ | 13/50 [00:11<00:32, 1.12it/s]\n 28%|██▊ | 14/50 [00:12<00:32, 1.12it/s]\n 30%|███ | 15/50 [00:13<00:31, 1.12it/s]\n 32%|███▏ | 16/50 [00:14<00:30, 1.12it/s]\n 34%|███▍ | 17/50 [00:15<00:29, 1.12it/s]\n 36%|███▌ | 18/50 [00:16<00:28, 1.12it/s]\n 38%|███▊ | 19/50 [00:16<00:27, 1.12it/s]\n 40%|████ | 20/50 [00:17<00:26, 1.12it/s]\n 42%|████▏ | 21/50 [00:18<00:25, 1.12it/s]\n 44%|████▍ | 22/50 [00:19<00:24, 1.12it/s]\n 46%|████▌ | 23/50 [00:20<00:24, 1.12it/s]\n 48%|████▊ | 24/50 [00:21<00:23, 1.12it/s]\n 50%|█████ | 25/50 [00:22<00:22, 1.12it/s]\n 52%|█████▏ | 26/50 [00:23<00:21, 1.12it/s]\n 54%|█████▍ | 27/50 [00:24<00:20, 1.12it/s]\n 56%|█████▌ | 28/50 [00:24<00:19, 1.12it/s]\n 58%|█████▊ | 29/50 [00:25<00:18, 1.12it/s]\n 60%|██████ | 30/50 [00:26<00:17, 1.12it/s]\n 62%|██████▏ | 31/50 [00:27<00:16, 1.12it/s]\n 64%|██████▍ | 32/50 [00:28<00:16, 1.12it/s]\n 66%|██████▌ | 33/50 [00:29<00:15, 1.12it/s]\n 68%|██████▊ | 34/50 [00:30<00:14, 1.12it/s]\n 70%|███████ | 35/50 [00:31<00:13, 1.12it/s]\n 72%|███████▏ | 36/50 [00:32<00:12, 1.12it/s]\n 74%|███████▍ | 37/50 [00:32<00:11, 1.12it/s]\n 76%|███████▌ | 38/50 [00:33<00:10, 1.12it/s]\n 78%|███████▊ | 39/50 [00:34<00:09, 1.12it/s]\n 80%|████████ | 40/50 [00:35<00:08, 1.12it/s]\n 82%|████████▏ | 41/50 [00:36<00:08, 1.12it/s]\n 84%|████████▍ | 42/50 [00:37<00:07, 1.12it/s]\n 86%|████████▌ | 43/50 [00:38<00:06, 1.12it/s]\n 88%|████████▊ | 44/50 [00:39<00:05, 1.12it/s]\n 90%|█████████ | 45/50 [00:40<00:04, 1.12it/s]\n 92%|█████████▏| 46/50 [00:41<00:03, 1.12it/s]\n 94%|█████████▍| 47/50 [00:41<00:02, 1.12it/s]\n 96%|█████████▌| 48/50 [00:42<00:01, 1.12it/s]\n 98%|█████████▊| 49/50 [00:43<00:00, 1.12it/s]\n100%|██████████| 50/50 [00:44<00:00, 1.12it/s]\n100%|██████████| 50/50 [00:44<00:00, 1.12it/s]\n[INFO] Time taken: 44.77764296531677 seconds.",
"metrics": {
"predict_time": 45.750611,
"total_time": 45.782965
},
"output": "https://replicate.delivery/pbxt/bFdwZjPFqc7GPhkgRAtqq6UlR2PC41JSM1vmVakRS7w2mqhE/result.png",
"started_at": "2023-12-28T04:08:14.189880Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/2mog35lbq2xztefdcmgjs7dprq",
"cancel": "https://api.replicate.com/v1/predictions/2mog35lbq2xztefdcmgjs7dprq/cancel"
},
"version": "bddc09369f9e622518f6d11daff26723a513714e08830ed053660d8ac44ffe88"
}Generated in
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[INFO] Time taken: 44.77764296531677 seconds.