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anotherjesse /zeroscope-v2-xl:9f747673
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=anotherjesse/zeroscope-v2-xl
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 anotherjesse/zeroscope-v2-xl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"anotherjesse/zeroscope-v2-xl:9f747673945c62801b13b84701c783929c0ee784e4748ec062204894dda1a351",
{
input: {
fps: 24,
model: "xl",
width: 1024,
height: 576,
prompt: "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
batch_size: 1,
num_frames: 24,
init_weight: 0.5,
guidance_scale: 17.5,
negative_prompt: "very blue, dust, noisy, washed out, ugly, distorted, broken",
remove_watermark: false,
num_inference_steps: 50
}
}
);
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 anotherjesse/zeroscope-v2-xl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"anotherjesse/zeroscope-v2-xl:9f747673945c62801b13b84701c783929c0ee784e4748ec062204894dda1a351",
input={
"fps": 24,
"model": "xl",
"width": 1024,
"height": 576,
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
"batch_size": 1,
"num_frames": 24,
"init_weight": 0.5,
"guidance_scale": 17.5,
"negative_prompt": "very blue, dust, noisy, washed out, ugly, distorted, broken",
"remove_watermark": False,
"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 anotherjesse/zeroscope-v2-xl 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": "9f747673945c62801b13b84701c783929c0ee784e4748ec062204894dda1a351",
"input": {
"fps": 24,
"model": "xl",
"width": 1024,
"height": 576,
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
"batch_size": 1,
"num_frames": 24,
"init_weight": 0.5,
"guidance_scale": 17.5,
"negative_prompt": "very blue, dust, noisy, washed out, ugly, distorted, broken",
"remove_watermark": false,
"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": "2023-06-25T00:06:59.201740Z",
"created_at": "2023-06-25T00:03:12.598367Z",
"data_removed": false,
"error": null,
"id": "7pan64dbqju3dxr6qsnxnekk5q",
"input": {
"fps": 24,
"fast": false,
"width": 1024,
"height": 576,
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
"num_frames": 24,
"guidance_scale": 17.5,
"negative_prompt": "very blue, dust, noisy, washed out, ugly, distorted, broken",
"num_inference_steps": 50
},
"logs": "Using seed: 21459\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:02<02:18, 2.83s/it]\n 4%|▍ | 2/50 [00:04<01:41, 2.11s/it]\n 6%|▌ | 3/50 [00:06<01:28, 1.88s/it]\n 8%|▊ | 4/50 [00:07<01:21, 1.77s/it]\n 10%|█ | 5/50 [00:09<01:16, 1.71s/it]\n 12%|█▏ | 6/50 [00:10<01:13, 1.67s/it]\n 14%|█▍ | 7/50 [00:12<01:10, 1.65s/it]\n 16%|█▌ | 8/50 [00:14<01:08, 1.63s/it]\n 18%|█▊ | 9/50 [00:15<01:06, 1.63s/it]\n 20%|██ | 10/50 [00:17<01:04, 1.62s/it]\n 22%|██▏ | 11/50 [00:18<01:02, 1.61s/it]\n 24%|██▍ | 12/50 [00:20<01:01, 1.61s/it]\n 26%|██▌ | 13/50 [00:22<00:59, 1.61s/it]\n 28%|██▊ | 14/50 [00:23<00:57, 1.61s/it]\n 30%|███ | 15/50 [00:25<00:56, 1.61s/it]\n 32%|███▏ | 16/50 [00:26<00:54, 1.61s/it]\n 34%|███▍ | 17/50 [00:28<00:53, 1.61s/it]\n 36%|███▌ | 18/50 [00:30<00:51, 1.61s/it]\n 38%|███▊ | 19/50 [00:31<00:49, 1.61s/it]\n 40%|████ | 20/50 [00:33<00:48, 1.61s/it]\n 42%|████▏ | 21/50 [00:34<00:46, 1.61s/it]\n 44%|████▍ | 22/50 [00:36<00:45, 1.61s/it]\n 46%|████▌ | 23/50 [00:38<00:43, 1.61s/it]\n 48%|████▊ | 24/50 [00:39<00:41, 1.61s/it]\n 50%|█████ | 25/50 [00:41<00:40, 1.61s/it]\n 52%|█████▏ | 26/50 [00:42<00:38, 1.61s/it]\n 54%|█████▍ | 27/50 [00:44<00:37, 1.61s/it]\n 56%|█████▌ | 28/50 [00:46<00:35, 1.61s/it]\n 58%|█████▊ | 29/50 [00:47<00:33, 1.61s/it]\n 60%|██████ | 30/50 [00:49<00:32, 1.61s/it]\n 62%|██████▏ | 31/50 [00:51<00:30, 1.61s/it]\n 64%|██████▍ | 32/50 [00:52<00:28, 1.61s/it]\n 66%|██████▌ | 33/50 [00:54<00:27, 1.61s/it]\n 68%|██████▊ | 34/50 [00:55<00:25, 1.61s/it]\n 70%|███████ | 35/50 [00:57<00:24, 1.61s/it]\n 72%|███████▏ | 36/50 [00:59<00:22, 1.61s/it]\n 74%|███████▍ | 37/50 [01:00<00:20, 1.61s/it]\n 76%|███████▌ | 38/50 [01:02<00:19, 1.61s/it]\n 78%|███████▊ | 39/50 [01:03<00:17, 1.61s/it]\n 80%|████████ | 40/50 [01:05<00:16, 1.61s/it]\n 82%|████████▏ | 41/50 [01:07<00:14, 1.61s/it]\n 84%|████████▍ | 42/50 [01:08<00:12, 1.61s/it]\n 86%|████████▌ | 43/50 [01:10<00:11, 1.61s/it]\n 88%|████████▊ | 44/50 [01:12<00:09, 1.61s/it]\n 90%|█████████ | 45/50 [01:13<00:08, 1.61s/it]\n 92%|█████████▏| 46/50 [01:15<00:06, 1.61s/it]\n 94%|█████████▍| 47/50 [01:16<00:04, 1.61s/it]\n 96%|█████████▌| 48/50 [01:18<00:03, 1.61s/it]\n 98%|█████████▊| 49/50 [01:20<00:01, 1.61s/it]\n100%|██████████| 50/50 [01:21<00:00, 1.61s/it]\n100%|██████████| 50/50 [01:21<00:00, 1.63s/it]",
"metrics": {
"predict_time": 88.371825,
"total_time": 226.603373
},
"output": "https://replicate.delivery/pbxt/BxOCqncnxzI9NZZdsRd3N7i1IO2uNH053x6pGrOWtQnI3USE/out.mp4",
"started_at": "2023-06-25T00:05:30.829915Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/7pan64dbqju3dxr6qsnxnekk5q",
"cancel": "https://api.replicate.com/v1/predictions/7pan64dbqju3dxr6qsnxnekk5q/cancel"
},
"version": "1f0dd155aeff719af56f4a2e516c7f7d4c91a38c7b8e9e81808e7c71bde9b868"
}Generated in
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100%|██████████| 50/50 [01:21<00:00, 1.63s/it]This example was created by a different version, anotherjesse/zeroscope-v2-xl:1f0dd155.