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camenduru /open-sora-plan-512x512:83b03885
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=camenduru/open-sora-plan-512x512
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 camenduru/open-sora-plan-512x512 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"camenduru/open-sora-plan-512x512:83b03885f983bd923e70afa5a51e2369d55aa34d2439014a484df3107a4322ca",
{
input: {
seed: 0,
prompt: "A quiet beach at dawn, the waves gently lapping at the shore and the sky painted in pastel hues.",
force_images: false,
sample_steps: 50,
guidance_scale: 10,
randomize_seed: true
}
}
);
console.log(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 camenduru/open-sora-plan-512x512 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"camenduru/open-sora-plan-512x512:83b03885f983bd923e70afa5a51e2369d55aa34d2439014a484df3107a4322ca",
input={
"seed": 0,
"prompt": "A quiet beach at dawn, the waves gently lapping at the shore and the sky painted in pastel hues.",
"force_images": False,
"sample_steps": 50,
"guidance_scale": 10,
"randomize_seed": True
}
)
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 camenduru/open-sora-plan-512x512 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": "83b03885f983bd923e70afa5a51e2369d55aa34d2439014a484df3107a4322ca",
"input": {
"seed": 0,
"prompt": "A quiet beach at dawn, the waves gently lapping at the shore and the sky painted in pastel hues.",
"force_images": false,
"sample_steps": 50,
"guidance_scale": 10,
"randomize_seed": true
}
}' \
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": "2024-04-07T14:07:26.169016Z",
"created_at": "2024-04-07T14:00:29.027000Z",
"data_removed": false,
"error": null,
"id": "fm0ye72ccdrgj0ceq3eawfaf3g",
"input": {
"seed": 0,
"prompt": "A quiet beach at dawn, the waves gently lapping at the shore and the sky painted in pastel hues.",
"force_images": false,
"sample_steps": 50,
"guidance_scale": 10,
"randomize_seed": true
},
"logs": "Setting `clean_caption=True` requires the ftfy library but it was not found in your environment. Checkout the instructions on the\ninstallation section: https://github.com/rspeer/python-ftfy/tree/master#installing and follow the ones\nthat match your environment. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\nSetting `clean_caption=True` requires the ftfy library but it was not found in your environment. Checkout the instructions on the\ninstallation section: https://github.com/rspeer/python-ftfy/tree/master#installing and follow the ones\nthat match your environment. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:11<09:03, 11.09s/it]\n 4%|▍ | 2/50 [00:12<04:10, 5.22s/it]\n 6%|▌ | 3/50 [00:13<02:36, 3.34s/it]\n 8%|▊ | 4/50 [00:14<01:52, 2.45s/it]\n 10%|█ | 5/50 [00:15<01:28, 1.97s/it]\n 12%|█▏ | 6/50 [00:16<01:13, 1.67s/it]\n 14%|█▍ | 7/50 [00:17<01:03, 1.49s/it]\n 16%|█▌ | 8/50 [00:18<00:57, 1.36s/it]\n 18%|█▊ | 9/50 [00:19<00:52, 1.28s/it]\n 20%|██ | 10/50 [00:21<00:49, 1.23s/it]\n 22%|██▏ | 11/50 [00:22<00:46, 1.19s/it]\n 24%|██▍ | 12/50 [00:23<00:44, 1.16s/it]\n 26%|██▌ | 13/50 [00:24<00:42, 1.14s/it]\n 28%|██▊ | 14/50 [00:25<00:40, 1.13s/it]\n 30%|███ | 15/50 [00:26<00:39, 1.12s/it]\n 32%|███▏ | 16/50 [00:27<00:38, 1.12s/it]\n 34%|███▍ | 17/50 [00:28<00:36, 1.12s/it]\n 36%|███▌ | 18/50 [00:29<00:35, 1.11s/it]\n 38%|███▊ | 19/50 [00:30<00:34, 1.11s/it]\n 40%|████ | 20/50 [00:32<00:33, 1.11s/it]\n 42%|████▏ | 21/50 [00:33<00:32, 1.11s/it]\n 44%|████▍ | 22/50 [00:34<00:31, 1.11s/it]\n 46%|████▌ | 23/50 [00:35<00:29, 1.11s/it]\n 48%|████▊ | 24/50 [00:36<00:28, 1.11s/it]\n 50%|█████ | 25/50 [00:37<00:27, 1.11s/it]\n 52%|█████▏ | 26/50 [00:38<00:26, 1.11s/it]\n 54%|█████▍ | 27/50 [00:39<00:25, 1.11s/it]\n 56%|█████▌ | 28/50 [00:40<00:24, 1.11s/it]\n 58%|█████▊ | 29/50 [00:42<00:23, 1.11s/it]\n 60%|██████ | 30/50 [00:43<00:22, 1.11s/it]\n 62%|██████▏ | 31/50 [00:44<00:21, 1.11s/it]\n 64%|██████▍ | 32/50 [00:45<00:20, 1.11s/it]\n 66%|██████▌ | 33/50 [00:46<00:18, 1.11s/it]\n 68%|██████▊ | 34/50 [00:47<00:17, 1.11s/it]\n 70%|███████ | 35/50 [00:48<00:16, 1.11s/it]\n 72%|███████▏ | 36/50 [00:49<00:15, 1.11s/it]\n 74%|███████▍ | 37/50 [00:50<00:14, 1.11s/it]\n 76%|███████▌ | 38/50 [00:52<00:13, 1.11s/it]\n 78%|███████▊ | 39/50 [00:53<00:12, 1.11s/it]\n 80%|████████ | 40/50 [00:54<00:11, 1.11s/it]\n 82%|████████▏ | 41/50 [00:55<00:10, 1.11s/it]\n 84%|████████▍ | 42/50 [00:56<00:08, 1.12s/it]\n 86%|████████▌ | 43/50 [00:57<00:07, 1.12s/it]\n 88%|████████▊ | 44/50 [00:58<00:06, 1.11s/it]\n 90%|█████████ | 45/50 [00:59<00:05, 1.11s/it]\n 92%|█████████▏| 46/50 [01:00<00:04, 1.11s/it]\n 94%|█████████▍| 47/50 [01:02<00:03, 1.11s/it]\n 96%|█████████▌| 48/50 [01:03<00:02, 1.11s/it]\n 98%|█████████▊| 49/50 [01:04<00:01, 1.11s/it]\n100%|██████████| 50/50 [01:05<00:00, 1.11s/it]\n100%|██████████| 50/50 [01:05<00:00, 1.31s/it]",
"metrics": {
"predict_time": 76.30664,
"total_time": 417.142016
},
"output": "https://replicate.delivery/pbxt/t2EtLj0MWhp4OJoJ0ymohD9NDpnKzt0eb9hDyxQsqrZO1CUJA/tmp.mp4",
"started_at": "2024-04-07T14:06:09.862376Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/fm0ye72ccdrgj0ceq3eawfaf3g",
"cancel": "https://api.replicate.com/v1/predictions/fm0ye72ccdrgj0ceq3eawfaf3g/cancel"
},
"version": "83b03885f983bd923e70afa5a51e2369d55aa34d2439014a484df3107a4322ca"
}Generated in
Setting `clean_caption=True` requires the ftfy library but it was not found in your environment. Checkout the instructions on the
installation section: https://github.com/rspeer/python-ftfy/tree/master#installing and follow the ones
that match your environment. Please note that you may need to restart your runtime after installation.
Setting `clean_caption` to False...
Setting `clean_caption=True` requires the ftfy library but it was not found in your environment. Checkout the instructions on the
installation section: https://github.com/rspeer/python-ftfy/tree/master#installing and follow the ones
that match your environment. Please note that you may need to restart your runtime after installation.
Setting `clean_caption` to False...
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