defaultAn astronaut riding a horse
typetext
{
"batch_size": 1,
"fps": 24,
"guidance_scale": 12.5,
"height": 576,
"init_video": "https://replicate.delivery/pbxt/J5iIA8MYk60mpl917rS9NEbAiULi3PpODpV07pcryBrpR46g/clown_fish_guidance_scale_1250.mp4",
"init_weight": 0.2,
"model": "xl",
"negative_prompt": "very blue, dust, noisy, washed out, ugly, distorted, broken",
"num_frames": 24,
"num_inference_steps": 50,
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
"width": 1024
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_MSI**********************************
This is your API token. Keep it to yourself.
import Replicate from "replicate";
import fs from "node:fs";
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:71996d331e8ede8ef7bd76eba9fae076d31792e4ddf4ad057779b443d6aea62f",
{
input: {
batch_size: 1,
fps: 24,
guidance_scale: 12.5,
height: 576,
init_video: "https://replicate.delivery/pbxt/J5iIA8MYk60mpl917rS9NEbAiULi3PpODpV07pcryBrpR46g/clown_fish_guidance_scale_1250.mp4",
init_weight: 0.2,
model: "xl",
negative_prompt: "very blue, dust, noisy, washed out, ugly, distorted, broken",
num_frames: 24,
num_inference_steps: 50,
prompt: "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
width: 1024
}
}
);
// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output[0]);
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=r8_MSI**********************************
This is your API token. Keep it to yourself.
import replicate
Run 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:71996d331e8ede8ef7bd76eba9fae076d31792e4ddf4ad057779b443d6aea62f",
input={
"batch_size": 1,
"fps": 24,
"guidance_scale": 12.5,
"height": 576,
"init_video": "https://replicate.delivery/pbxt/J5iIA8MYk60mpl917rS9NEbAiULi3PpODpV07pcryBrpR46g/clown_fish_guidance_scale_1250.mp4",
"init_weight": 0.2,
"model": "xl",
"negative_prompt": "very blue, dust, noisy, washed out, ugly, distorted, broken",
"num_frames": 24,
"num_inference_steps": 50,
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
"width": 1024
}
)
# To access the file URL:
print(output[0].url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_MSI**********************************
This is your API token. Keep it to yourself.
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": "anotherjesse/zeroscope-v2-xl:71996d331e8ede8ef7bd76eba9fae076d31792e4ddf4ad057779b443d6aea62f",
"input": {
"batch_size": 1,
"fps": 24,
"guidance_scale": 12.5,
"height": 576,
"init_video": "https://replicate.delivery/pbxt/J5iIA8MYk60mpl917rS9NEbAiULi3PpODpV07pcryBrpR46g/clown_fish_guidance_scale_1250.mp4",
"init_weight": 0.2,
"model": "xl",
"negative_prompt": "very blue, dust, noisy, washed out, ugly, distorted, broken",
"num_frames": 24,
"num_inference_steps": 50,
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
"width": 1024
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{
"id": "dujigjlbxyagw5fxctrde6tthq",
"model": "anotherjesse/zeroscope-v2-xl",
"version": "71996d331e8ede8ef7bd76eba9fae076d31792e4ddf4ad057779b443d6aea62f",
"input": {
"batch_size": 1,
"fps": 24,
"guidance_scale": 12.5,
"height": 576,
"init_video": "https://replicate.delivery/pbxt/J5iIA8MYk60mpl917rS9NEbAiULi3PpODpV07pcryBrpR46g/clown_fish_guidance_scale_1250.mp4",
"init_weight": 0.2,
"model": "xl",
"negative_prompt": "very blue, dust, noisy, washed out, ugly, distorted, broken",
"num_frames": 24,
"num_inference_steps": 50,
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic",
"width": 1024
},
"logs": "Using seed: 47391\ninit_video 255463\n/root/.pyenv/versions/3.10.12/lib/python3.10/site-packages/diffusers/configuration_utils.py:135: FutureWarning: Accessing config attribute `num_train_timesteps` directly via 'DPMSolverMultistepScheduler' object attribute is deprecated. Please access 'num_train_timesteps' over 'DPMSolverMultistepScheduler's config object instead, e.g. 'scheduler.config.num_train_timesteps'.\ndeprecate(\"direct config name access\", \"1.0.0\", deprecation_message, standard_warn=False)\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:01<01:13, 1.88s/it]\n 5%|▌ | 2/40 [00:03<01:11, 1.88s/it]\n 8%|▊ | 3/40 [00:05<01:09, 1.88s/it]\n 10%|█ | 4/40 [00:07<01:07, 1.88s/it]\n 12%|█▎ | 5/40 [00:09<01:05, 1.88s/it]\n 15%|█▌ | 6/40 [00:11<01:04, 1.88s/it]\n 18%|█▊ | 7/40 [00:13<01:02, 1.88s/it]\n 20%|██ | 8/40 [00:15<01:00, 1.88s/it]\n 22%|██▎ | 9/40 [00:16<00:58, 1.89s/it]\n 25%|██▌ | 10/40 [00:18<00:56, 1.89s/it]\n 28%|██▊ | 11/40 [00:20<00:54, 1.89s/it]\n 30%|███ | 12/40 [00:22<00:52, 1.89s/it]\n 32%|███▎ | 13/40 [00:24<00:50, 1.89s/it]\n 35%|███▌ | 14/40 [00:26<00:49, 1.89s/it]\n 38%|███▊ | 15/40 [00:28<00:47, 1.89s/it]\n 40%|████ | 16/40 [00:30<00:45, 1.89s/it]\n 42%|████▎ | 17/40 [00:32<00:43, 1.89s/it]\n 45%|████▌ | 18/40 [00:33<00:41, 1.89s/it]\n 48%|████▊ | 19/40 [00:35<00:39, 1.89s/it]\n 50%|█████ | 20/40 [00:37<00:37, 1.89s/it]\n 52%|█████▎ | 21/40 [00:39<00:35, 1.89s/it]\n 55%|█████▌ | 22/40 [00:41<00:33, 1.89s/it]\n 57%|█████▊ | 23/40 [00:43<00:32, 1.89s/it]\n 60%|██████ | 24/40 [00:45<00:30, 1.89s/it]\n 62%|██████▎ | 25/40 [00:47<00:28, 1.89s/it]\n 65%|██████▌ | 26/40 [00:49<00:26, 1.89s/it]\n 68%|██████▊ | 27/40 [00:50<00:24, 1.89s/it]\n 70%|███████ | 28/40 [00:52<00:22, 1.89s/it]\n 72%|███████▎ | 29/40 [00:54<00:20, 1.89s/it]\n 75%|███████▌ | 30/40 [00:56<00:18, 1.89s/it]\n 78%|███████▊ | 31/40 [00:58<00:17, 1.89s/it]\n 80%|████████ | 32/40 [01:00<00:15, 1.89s/it]\n 82%|████████▎ | 33/40 [01:02<00:13, 1.89s/it]\n 85%|████████▌ | 34/40 [01:04<00:11, 1.89s/it]\n 88%|████████▊ | 35/40 [01:06<00:09, 1.89s/it]\n 90%|█████████ | 36/40 [01:07<00:07, 1.89s/it]\n 92%|█████████▎| 37/40 [01:09<00:05, 1.89s/it]\n 95%|█████████▌| 38/40 [01:11<00:03, 1.89s/it]\n 98%|█████████▊| 39/40 [01:13<00:01, 1.89s/it]\n100%|██████████| 40/40 [01:15<00:00, 1.89s/it]\n100%|██████████| 40/40 [01:15<00:00, 1.89s/it]",
"output": [
"https://replicate.delivery/pbxt/NoOzw78kex3JPy0vHJeNUf96K6BHOxkJv3s7JPjiEe7uRfYJC/output-0.mp4"
],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2023-06-30T12:29:56.523904Z",
"started_at": "2023-06-30T12:29:56.502896Z",
"completed_at": "2023-06-30T12:31:24.160569Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/dujigjlbxyagw5fxctrde6tthq/cancel",
"get": "https://api.replicate.com/v1/predictions/dujigjlbxyagw5fxctrde6tthq"
},
"metrics": {
"predict_time": 87.657673,
"total_time": 87.636665
}
}