Prediction

Model

wcarle/stable-diffusion-videos:d80e8dbe

j5ykuseosjdzpajbz5u4onuwze

Status

Succeeded

Source

Web

Hardware

–

Total duration

18m 23s

Created

over 2 years ago by wcarle

Webhook

–

Input

prompts: a cat | a dog | a horse
scheduler: klms
num_inference_steps: 30
guidance_scale: 7.5
num_steps: 50
fps: 15

{
  "fps": 15,
  "guidance_scale": 7.5,
  "num_inference_steps": 30,
  "num_steps": 50,
  "prompts": "a cat | a dog | a horse",
  "scheduler": "klms"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_ExK**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run wcarle/stable-diffusion-videos using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "wcarle/stable-diffusion-videos:d80e8dbe5885d570087b782ff22cef888dcc1be7941a52c8ba82c7c9d884d845",
  {
    input: {
      fps: 15,
      guidance_scale: 7.5,
      num_inference_steps: 30,
      num_steps: 50,
      prompts: "a cat | a dog | a horse",
      scheduler: "klms"
    }
  }
);

// 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 replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_ExK**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run wcarle/stable-diffusion-videos using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "wcarle/stable-diffusion-videos:d80e8dbe5885d570087b782ff22cef888dcc1be7941a52c8ba82c7c9d884d845",
    input={
        "fps": 15,
        "guidance_scale": 7.5,
        "num_inference_steps": 30,
        "num_steps": 50,
        "prompts": "a cat | a dog | a horse",
        "scheduler": "klms"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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=r8_ExK**********************************

This is your API token. Keep it to yourself.

Run wcarle/stable-diffusion-videos 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": "wcarle/stable-diffusion-videos:d80e8dbe5885d570087b782ff22cef888dcc1be7941a52c8ba82c7c9d884d845",
    "input": {
      "fps": 15,
      "guidance_scale": 7.5,
      "num_inference_steps": 30,
      "num_steps": 50,
      "prompts": "a cat | a dog | a horse",
      "scheduler": "klms"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "id": "j5ykuseosjdzpajbz5u4onuwze",
  "model": "wcarle/stable-diffusion-videos",
  "version": "d80e8dbe5885d570087b782ff22cef888dcc1be7941a52c8ba82c7c9d884d845",
  "input": {
    "fps": 15,
    "guidance_scale": 7.5,
    "num_inference_steps": 30,
    "num_steps": 50,
    "prompts": "a cat | a dog | a horse",
    "scheduler": "klms"
  },
  "logs": "Setting Random seeds.\nSeeds used for prompts are:\na cat: 36643\na dog: 56866\na horse: 38898\n  0%|          | 0/30 [00:00<?, ?it/s]\n  3%|▎         | 1/30 [00:02<01:17,  2.66s/it]\n  7%|▋         | 2/30 [00:02<00:34,  1.23s/it]\n 10%|█         | 3/30 [00:03<00:21,  1.28it/s]\n 13%|█▎        | 4/30 [00:03<00:14,  1.75it/s]\n 17%|█▋        | 5/30 [00:03<00:11,  2.20it/s]\n 20%|██        | 6/30 [00:03<00:09,  2.61it/s]\n 23%|██▎       | 7/30 [00:04<00:07,  2.97it/s]\n 27%|██▋       | 8/30 [00:04<00:06,  3.24it/s]\n 30%|███       | 9/30 [00:04<00:06,  3.46it/s]\n 33%|███▎      | 10/30 [00:04<00:05,  3.65it/s]\n 37%|███▋      | 11/30 [00:05<00:05,  3.76it/s]\n 40%|████      | 12/30 [00:05<00:04,  3.84it/s]\n 43%|████▎     | 13/30 [00:05<00:04,  3.90it/s]\n 47%|████▋     | 14/30 [00:05<00:04,  3.96it/s]\n 50%|█████     | 15/30 [00:06<00:03,  3.99it/s]\n 53%|█████▎    | 16/30 [00:06<00:03,  4.02it/s]\n 57%|█████▋    | 17/30 [00:06<00:03,  4.04it/s]\n 60%|██████    | 18/30 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3.77it/s]\n100%|██████████| 30/30 [00:07<00:00,  3.77it/s]\n100%|██████████| 30/30 [00:07<00:00,  3.76it/s]\n  0%|          | 0/30 [00:00<?, ?it/s]\n  3%|▎         | 1/30 [00:00<00:07,  3.86it/s]\n  7%|▋         | 2/30 [00:00<00:07,  3.82it/s]\n 10%|█         | 3/30 [00:00<00:07,  3.80it/s]\n 13%|█▎        | 4/30 [00:01<00:07,  3.69it/s]\n 17%|█▋        | 5/30 [00:01<00:06,  3.71it/s]\n 20%|██        | 6/30 [00:01<00:06,  3.73it/s]\n 23%|██▎       | 7/30 [00:01<00:06,  3.73it/s]\n 27%|██▋       | 8/30 [00:02<00:05,  3.74it/s]\n 30%|███       | 9/30 [00:02<00:05,  3.76it/s]\n 33%|███▎      | 10/30 [00:02<00:05,  3.76it/s]\n 37%|███▋      | 11/30 [00:02<00:05,  3.77it/s]\n 40%|████      | 12/30 [00:03<00:04,  3.77it/s]\n 43%|████▎     | 13/30 [00:03<00:04,  3.77it/s]\n 47%|████▋     | 14/30 [00:03<00:04,  3.77it/s]\n 50%|█████     | 15/30 [00:03<00:03,  3.75it/s]\n 53%|█████▎    | 16/30 [00:04<00:03,  3.76it/s]\n 57%|█████▋    | 17/30 [00:04<00:03,  3.76it/s]\n 60%|██████    | 18/30 [00:04<00:03,  3.77it/s]\n 63%|██████▎   | 19/30 [00:05<00:02,  3.78it/s]\n 67%|██████▋   | 20/30 [00:05<00:02,  3.78it/s]\n 70%|███████   | 21/30 [00:05<00:02,  3.77it/s]\n 73%|███████▎  | 22/30 [00:05<00:02,  3.77it/s]\n 77%|███████▋  | 23/30 [00:06<00:01,  3.77it/s]\n 80%|████████  | 24/30 [00:06<00:01,  3.76it/s]\n 83%|████████▎ | 25/30 [00:06<00:01,  3.75it/s]\n 87%|████████▋ | 26/30 [00:06<00:01,  3.76it/s]\n 90%|█████████ | 27/30 [00:07<00:00,  3.76it/s]\n 93%|█████████▎| 28/30 [00:07<00:00,  3.76it/s]\n 97%|█████████▋| 29/30 [00:07<00:00,  3.77it/s]\n100%|██████████| 30/30 [00:07<00:00,  3.78it/s]\n100%|██████████| 30/30 [00:07<00:00,  3.76it/s]",
  "output": "https://replicate.delivery/pbxt/SuEOZdHqJ3ZJCNLyroDGPpCUYNCcUE6hEPHLNnAaUeTBM9WIA/out.mp4",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-04-02T21:12:20.569797Z",
  "started_at": "2023-04-02T21:16:30.666086Z",
  "completed_at": "2023-04-02T21:30:43.209013Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/j5ykuseosjdzpajbz5u4onuwze/cancel",
    "get": "https://api.replicate.com/v1/predictions/j5ykuseosjdzpajbz5u4onuwze"
  },
  "metrics": {
    "predict_time": 852.542927,
    "total_time": 1102.639216
  }
}

Generated in

14 minutes 13 seconds

Tweak it Report

Setting Random seeds. Seeds used for prompts are: a cat: 36643 a dog: 56866 a horse: 38898 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:02<01:17, 2.66s/it] 7%|▋ | 2/30 [00:02<00:34, 1.23s/it] 10%|█ | 3/30 [00:03<00:21, 1.28it/s] 13%|█▎ | 4/30 [00:03<00:14, 1.75it/s] 17%|█▋ | 5/30 [00:03<00:11, 2.20it/s] 20%|██ | 6/30 [00:03<00:09, 2.61it/s] 23%|██▎ | 7/30 [00:04<00:07, 2.97it/s] 27%|██▋ | 8/30 [00:04<00:06, 3.24it/s] 30%|███ | 9/30 [00:04<00:06, 3.46it/s] 33%|███▎ | 10/30 [00:04<00:05, 3.65it/s] 37%|███▋ | 11/30 [00:05<00:05, 3.76it/s] 40%|████ | 12/30 [00:05<00:04, 3.84it/s] 43%|████▎ | 13/30 [00:05<00:04, 3.90it/s] 47%|████▋ | 14/30 [00:05<00:04, 3.96it/s] 50%|█████ | 15/30 [00:06<00:03, 3.99it/s] 53%|█████▎ | 16/30 [00:06<00:03, 4.02it/s] 57%|█████▋ | 17/30 [00:06<00:03, 4.04it/s] 60%|██████ | 18/30 [00:06<00:02, 4.06it/s] 63%|██████▎ | 19/30 [00:07<00:02, 4.06it/s] 67%|██████▋ | 20/30 [00:07<00:02, 4.07it/s] 70%|███████ | 21/30 [00:07<00:02, 4.07it/s] 73%|███████▎ | 22/30 [00:07<00:01, 4.06it/s] 77%|███████▋ | 23/30 [00:08<00:01, 4.06it/s] 80%|████████ | 24/30 [00:08<00:01, 4.05it/s] 83%|████████▎ | 25/30 [00:08<00:01, 4.06it/s] 87%|████████▋ | 26/30 [00:08<00:00, 4.06it/s] 90%|█████████ | 27/30 [00:09<00:00, 4.06it/s] 93%|█████████▎| 28/30 [00:09<00:00, 4.07it/s] 97%|█████████▋| 29/30 [00:09<00:00, 4.06it/s] 100%|██████████| 30/30 [00:09<00:00, 4.03it/s] 100%|██████████| 30/30 [00:09<00:00, 3.07it/s] 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 4.06it/s] 7%|▋ | 2/30 [00:00<00:06, 4.11it/s] 10%|█ | 3/30 [00:00<00:06, 4.09it/s] 13%|█▎ | 4/30 [00:00<00:06, 4.01it/s] 17%|█▋ | 5/30 [00:01<00:06, 4.04it/s] 20%|██ | 6/30 [00:01<00:05, 4.01it/s] 23%|██▎ | 7/30 [00:01<00:05, 4.03it/s] 27%|██▋ | 8/30 [00:01<00:05, 4.03it/s] 30%|███ | 9/30 [00:02<00:05, 4.03it/s] 33%|███▎ | 10/30 [00:02<00:04, 4.03it/s] 37%|███▋ | 11/30 [00:02<00:04, 4.04it/s] 40%|████ | 12/30 [00:02<00:04, 4.04it/s] 43%|████▎ | 13/30 [00:03<00:04, 4.03it/s] 47%|████▋ | 14/30 [00:03<00:03, 4.02it/s] 50%|█████ | 15/30 [00:03<00:03, 4.02it/s] 53%|█████▎ | 16/30 [00:03<00:03, 4.03it/s] 57%|█████▋ | 17/30 [00:04<00:03, 4.02it/s] 60%|██████ | 18/30 [00:04<00:02, 4.01it/s] 63%|██████▎ | 19/30 [00:04<00:02, 4.00it/s] 67%|██████▋ | 20/30 [00:04<00:02, 4.02it/s] 70%|███████ | 21/30 [00:05<00:02, 4.03it/s] 73%|███████▎ | 22/30 [00:05<00:01, 4.04it/s] 77%|███████▋ | 23/30 [00:05<00:01, 4.04it/s] 80%|████████ | 24/30 [00:05<00:01, 4.05it/s] 83%|████████▎ | 25/30 [00:06<00:01, 4.05it/s] 87%|████████▋ | 26/30 [00:06<00:00, 4.06it/s] 90%|█████████ | 27/30 [00:06<00:00, 4.06it/s] 93%|█████████▎| 28/30 [00:06<00:00, 4.05it/s] 97%|█████████▋| 29/30 [00:07<00:00, 4.06it/s] 100%|██████████| 30/30 [00:07<00:00, 4.05it/s] 100%|██████████| 30/30 [00:07<00:00, 4.04it/s] 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 4.08it/s] 7%|▋ | 2/30 [00:00<00:06, 4.11it/s] 10%|█ | 3/30 [00:00<00:06, 4.10it/s] 13%|█▎ | 4/30 [00:00<00:06, 4.02it/s] 17%|█▋ | 5/30 [00:01<00:06, 4.03it/s] 20%|██ | 6/30 [00:01<00:05, 4.04it/s] 23%|██▎ | 7/30 [00:01<00:05, 4.05it/s] 27%|██▋ | 8/30 [00:01<00:05, 4.03it/s] 30%|███ | 9/30 [00:02<00:05, 4.01it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.99it/s] 37%|███▋ | 11/30 [00:02<00:04, 3.99it/s] 40%|████ | 12/30 [00:02<00:04, 3.98it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.97it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.97it/s] 50%|█████ | 15/30 [00:03<00:03, 3.98it/s] 53%|█████▎ | 16/30 [00:03<00:03, 3.98it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.98it/s] 60%|██████ | 18/30 [00:04<00:03, 3.97it/s] 63%|██████▎ | 19/30 [00:04<00:02, 3.98it/s] 67%|██████▋ | 20/30 [00:04<00:02, 4.00it/s] 70%|███████ | 21/30 [00:05<00:02, 3.97it/s] 73%|███████▎ | 22/30 [00:05<00:02, 3.99it/s] 77%|███████▋ | 23/30 [00:05<00:01, 4.01it/s] 80%|████████ | 24/30 [00:05<00:01, 4.00it/s] 83%|████████▎ | 25/30 [00:06<00:01, 4.00it/s] 87%|████████▋ | 26/30 [00:06<00:01, 3.99it/s] 90%|█████████ | 27/30 [00:06<00:00, 3.99it/s] 93%|█████████▎| 28/30 [00:06<00:00, 4.00it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.98it/s] 100%|██████████| 30/30 [00:07<00:00, 3.98it/s] 100%|██████████| 30/30 [00:07<00:00, 4.00it/s] 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 4.11it/s] 7%|▋ | 2/30 [00:00<00:06, 4.08it/s] 10%|█ | 3/30 [00:00<00:06, 4.09it/s] 13%|█▎ | 4/30 [00:00<00:06, 3.99it/s] 17%|█▋ | 5/30 [00:01<00:06, 4.00it/s] 20%|██ | 6/30 [00:01<00:06, 4.00it/s] 23%|██▎ | 7/30 [00:01<00:05, 3.97it/s] 27%|██▋ | 8/30 [00:01<00:05, 3.98it/s] 30%|███ | 9/30 [00:02<00:05, 3.98it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.97it/s] 37%|███▋ | 11/30 [00:02<00:04, 3.97it/s] 40%|████ | 12/30 [00:03<00:04, 3.96it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.97it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.97it/s] 50%|█████ | 15/30 [00:03<00:03, 3.97it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.97it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.96it/s] 60%|██████ | 18/30 [00:04<00:03, 3.96it/s] 63%|██████▎ | 19/30 [00:04<00:02, 3.96it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.95it/s] 70%|███████ | 21/30 [00:05<00:02, 3.95it/s] 73%|███████▎ | 22/30 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