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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: 107,
prompt: "Envision a portrait of a cute scientist owl in blue and gray outfit announcing their latest breakthrough discovery. his eyes are light brown. his attire is simple yet dignified",
img_width: 1024,
rrg_scale: 750,
img_height: 2048,
cosine_scale: 10,
guidance_scale: 10,
view_batch_size: 16,
negative_prompts: "blurry, ugly, poorly drawn, deformed",
resampling_new_p: 0.3,
resampling_steps: 8,
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": 107,
"prompt": "Envision a portrait of a cute scientist owl in blue and gray outfit announcing their latest breakthrough discovery. his eyes are light brown. his attire is simple yet dignified",
"img_width": 1024,
"rrg_scale": 750,
"img_height": 2048,
"cosine_scale": 10,
"guidance_scale": 10,
"view_batch_size": 16,
"negative_prompts": "blurry, ugly, poorly drawn, deformed",
"resampling_new_p": 0.3,
"resampling_steps": 8,
"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": 107,
"prompt": "Envision a portrait of a cute scientist owl in blue and gray outfit announcing their latest breakthrough discovery. his eyes are light brown. his attire is simple yet dignified",
"img_width": 1024,
"rrg_scale": 750,
"img_height": 2048,
"cosine_scale": 10,
"guidance_scale": 10,
"view_batch_size": 16,
"negative_prompts": "blurry, ugly, poorly drawn, deformed",
"resampling_new_p": 0.3,
"resampling_steps": 8,
"num_inference_steps": 50
}
}' \
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.
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terms of service and privacy policy
Output
{
"completed_at": "2024-09-11T23:25:12.790185Z",
"created_at": "2024-09-11T23:19:45.383000Z",
"data_removed": false,
"error": null,
"id": "f21dafdzwxrgg0chwdh8bf912g",
"input": {
"seed": 107,
"prompt": "Envision a portrait of a cute scientist owl in blue and gray outfit announcing their latest breakthrough discovery. his eyes are light brown. his attire is simple yet dignified",
"img_width": 1024,
"rrg_scale": 750,
"img_height": 2048,
"cosine_scale": 10,
"guidance_scale": 10,
"view_batch_size": 16,
"negative_prompts": "blurry, ugly, poorly drawn, deformed",
"resampling_new_p": 0.3,
"resampling_steps": 8,
"num_inference_steps": 50
},
"logs": "0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:06<05:17, 6.49s/it]\n 4%|▍ | 2/50 [00:12<05:11, 6.49s/it]\n 6%|▌ | 3/50 [00:19<05:04, 6.48s/it]\n 8%|▊ | 4/50 [00:26<04:59, 6.51s/it]\n 10%|█ | 5/50 [00:32<04:52, 6.50s/it]\n 12%|█▏ | 6/50 [00:38<04:45, 6.50s/it]\n 14%|█▍ | 7/50 [00:45<04:39, 6.50s/it]\n 16%|█▌ | 8/50 [00:51<04:32, 6.50s/it]\n 18%|█▊ | 9/50 [00:58<04:26, 6.49s/it]\n 20%|██ | 10/50 [01:04<04:19, 6.49s/it]\n 22%|██▏ | 11/50 [01:11<04:13, 6.49s/it]\n 24%|██▍ | 12/50 [01:17<04:06, 6.49s/it]\n 26%|██▌ | 13/50 [01:24<04:00, 6.49s/it]\n 28%|██▊ | 14/50 [01:30<03:53, 6.49s/it]\n 30%|███ | 15/50 [01:37<03:47, 6.49s/it]\n 32%|███▏ | 16/50 [01:43<03:40, 6.50s/it]\n 34%|███▍ | 17/50 [01:50<03:35, 6.52s/it]\n 36%|███▌ | 18/50 [01:57<03:28, 6.52s/it]\n 38%|███▊ | 19/50 [02:03<03:21, 6.51s/it]\n 40%|████ | 20/50 [02:10<03:15, 6.51s/it]\n 42%|████▏ | 21/50 [02:16<03:08, 6.52s/it]\n 44%|████▍ | 22/50 [02:23<03:02, 6.51s/it]\n 46%|████▌ | 23/50 [02:29<02:55, 6.51s/it]\n 48%|████▊ | 24/50 [02:36<02:49, 6.51s/it]\n 50%|█████ | 25/50 [02:42<02:42, 6.51s/it]\n 52%|█████▏ | 26/50 [02:49<02:36, 6.50s/it]\n 54%|█████▍ | 27/50 [02:55<02:29, 6.50s/it]\n 56%|█████▌ | 28/50 [03:02<02:22, 6.50s/it]\n 58%|█████▊ | 29/50 [03:08<02:16, 6.50s/it]\n 60%|██████ | 30/50 [03:15<02:09, 6.50s/it]\n 62%|██████▏ | 31/50 [03:21<02:03, 6.50s/it]\n 64%|██████▍ | 32/50 [03:28<01:56, 6.50s/it]\n 66%|██████▌ | 33/50 [03:34<01:50, 6.50s/it]\n 68%|██████▊ | 34/50 [03:41<01:43, 6.50s/it]\n 70%|███████ | 35/50 [03:47<01:37, 6.51s/it]\n 72%|███████▏ | 36/50 [03:54<01:31, 6.50s/it]\n 74%|███████▍ | 37/50 [04:00<01:24, 6.50s/it]\n 76%|███████▌ | 38/50 [04:07<01:18, 6.50s/it]\n 78%|███████▊ | 39/50 [04:13<01:11, 6.50s/it]\n 80%|████████ | 40/50 [04:20<01:05, 6.50s/it]\n 82%|████████▏ | 41/50 [04:26<00:58, 6.51s/it]\n 84%|████████▍ | 42/50 [04:33<00:52, 6.51s/it]\n 86%|████████▌ | 43/50 [04:39<00:45, 6.51s/it]\n 88%|████████▊ | 44/50 [04:46<00:39, 6.51s/it]\n 90%|█████████ | 45/50 [04:52<00:32, 6.54s/it]\n 92%|█████████▏| 46/50 [04:59<00:26, 6.53s/it]\n 94%|█████████▍| 47/50 [05:05<00:19, 6.53s/it]\n 96%|█████████▌| 48/50 [05:12<00:13, 6.52s/it]\n 98%|█████████▊| 49/50 [05:18<00:06, 6.52s/it]\n100%|██████████| 50/50 [05:24<00:00, 6.13s/it]\n100%|██████████| 50/50 [05:24<00:00, 6.48s/it]\n[INFO] Time taken: 324.91242361068726 seconds.",
"metrics": {
"predict_time": 327.301337936,
"total_time": 327.407185
},
"output": "https://replicate.delivery/pbxt/cbb84nepXXQeDEs4vaFHfjYlKLd5xjSbMH9rgzadMfAcN2vNB/result.png",
"started_at": "2024-09-11T23:19:45.488848Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/f21dafdzwxrgg0chwdh8bf912g",
"cancel": "https://api.replicate.com/v1/predictions/f21dafdzwxrgg0chwdh8bf912g/cancel"
},
"version": "bddc09369f9e622518f6d11daff26723a513714e08830ed053660d8ac44ffe88"
}Generated in
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[INFO] Time taken: 324.91242361068726 seconds.