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georgedavila /cog-ltx-video:807fb8df
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=georgedavila/cog-ltx-video
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";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run georgedavila/cog-ltx-video using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189",
{
input: {
outFPS: 24,
myprompt: "A woman with long brown hair and light skin smiles at another woman with long blonde hair. The woman with brown hair wears a black jacket and has a small, barely noticeable mole on her right cheek. The camera angle is a close-up, focused on the woman with brown hair's face. The lighting is warm and natural, likely from the setting sun, casting a soft glow on the scene. The scene appears to be real-life footage.",
outWidth: 768,
outHeight: 512,
num_frames: 97,
num_outputs: 1,
guidanceScale: 3,
negative_prompt: "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted",
num_inference_steps: 60
}
}
);
// 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 georgedavila/cog-ltx-video using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189",
input={
"outFPS": 24,
"myprompt": "A woman with long brown hair and light skin smiles at another woman with long blonde hair. The woman with brown hair wears a black jacket and has a small, barely noticeable mole on her right cheek. The camera angle is a close-up, focused on the woman with brown hair's face. The lighting is warm and natural, likely from the setting sun, casting a soft glow on the scene. The scene appears to be real-life footage.",
"outWidth": 768,
"outHeight": 512,
"num_frames": 97,
"num_outputs": 1,
"guidanceScale": 3,
"negative_prompt": "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted",
"num_inference_steps": 60
}
)
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 georgedavila/cog-ltx-video 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": "georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189",
"input": {
"outFPS": 24,
"myprompt": "A woman with long brown hair and light skin smiles at another woman with long blonde hair. The woman with brown hair wears a black jacket and has a small, barely noticeable mole on her right cheek. The camera angle is a close-up, focused on the woman with brown hair\'s face. The lighting is warm and natural, likely from the setting sun, casting a soft glow on the scene. The scene appears to be real-life footage.",
"outWidth": 768,
"outHeight": 512,
"num_frames": 97,
"num_outputs": 1,
"guidanceScale": 3,
"negative_prompt": "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted",
"num_inference_steps": 60
}
}' \
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.
Sign in with GitHub
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2025-01-09T23:54:20.815155Z",
"created_at": "2025-01-09T23:53:51.397000Z",
"data_removed": false,
"error": null,
"id": "te08tpgr4nrm80cm9nyvkpz5n0",
"input": {
"outFPS": 24,
"myprompt": "A woman with long brown hair and light skin smiles at another woman with long blonde hair. The woman with brown hair wears a black jacket and has a small, barely noticeable mole on her right cheek. The camera angle is a close-up, focused on the woman with brown hair's face. The lighting is warm and natural, likely from the setting sun, casting a soft glow on the scene. The scene appears to be real-life footage.",
"outWidth": 768,
"outHeight": 512,
"num_frames": 97,
"num_outputs": 1,
"guidanceScale": 3,
"negative_prompt": "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted",
"num_inference_steps": 60
},
"logs": "Using seed: 12353\n 0%| | 0/60 [00:00<?, ?it/s]\n 2%|▏ | 1/60 [00:00<00:26, 2.20it/s]\n 3%|▎ | 2/60 [00:00<00:20, 2.87it/s]\n 5%|▌ | 3/60 [00:01<00:22, 2.52it/s]\n 7%|▋ | 4/60 [00:01<00:23, 2.38it/s]\n 8%|▊ | 5/60 [00:02<00:23, 2.30it/s]\n 10%|█ | 6/60 [00:02<00:23, 2.26it/s]\n 12%|█▏ | 7/60 [00:03<00:23, 2.24it/s]\n 13%|█▎ | 8/60 [00:03<00:23, 2.22it/s]\n 15%|█▌ | 9/60 [00:03<00:23, 2.21it/s]\n 17%|█▋ | 10/60 [00:04<00:22, 2.20it/s]\n 18%|█▊ | 11/60 [00:04<00:22, 2.20it/s]\n 20%|██ | 12/60 [00:05<00:21, 2.20it/s]\n 22%|██▏ | 13/60 [00:05<00:21, 2.20it/s]\n 23%|██▎ | 14/60 [00:06<00:20, 2.19it/s]\n 25%|██▌ | 15/60 [00:06<00:20, 2.19it/s]\n 27%|██▋ | 16/60 [00:07<00:20, 2.19it/s]\n 28%|██▊ | 17/60 [00:07<00:19, 2.19it/s]\n 30%|███ | 18/60 [00:08<00:19, 2.19it/s]\n 32%|███▏ | 19/60 [00:08<00:18, 2.19it/s]\n 33%|███▎ | 20/60 [00:08<00:18, 2.19it/s]\n 35%|███▌ | 21/60 [00:09<00:17, 2.19it/s]\n 37%|███▋ | 22/60 [00:09<00:17, 2.19it/s]\n 38%|███▊ | 23/60 [00:10<00:16, 2.19it/s]\n 40%|████ | 24/60 [00:10<00:16, 2.19it/s]\n 42%|████▏ | 25/60 [00:11<00:16, 2.19it/s]\n 43%|████▎ | 26/60 [00:11<00:15, 2.19it/s]\n 45%|████▌ | 27/60 [00:12<00:15, 2.19it/s]\n 47%|████▋ | 28/60 [00:12<00:14, 2.19it/s]\n 48%|████▊ | 29/60 [00:13<00:14, 2.18it/s]\n 50%|█████ | 30/60 [00:13<00:13, 2.18it/s]\n 52%|█████▏ | 31/60 [00:13<00:13, 2.18it/s]\n 53%|█████▎ | 32/60 [00:14<00:12, 2.18it/s]\n 55%|█████▌ | 33/60 [00:14<00:12, 2.18it/s]\n 57%|█████▋ | 34/60 [00:15<00:11, 2.18it/s]\n 58%|█████▊ | 35/60 [00:15<00:11, 2.18it/s]\n 60%|██████ | 36/60 [00:16<00:11, 2.18it/s]\n 62%|██████▏ | 37/60 [00:16<00:10, 2.18it/s]\n 63%|██████▎ | 38/60 [00:17<00:10, 2.18it/s]\n 65%|██████▌ | 39/60 [00:17<00:09, 2.18it/s]\n 67%|██████▋ | 40/60 [00:18<00:09, 2.18it/s]\n 68%|██████▊ | 41/60 [00:18<00:08, 2.18it/s]\n 70%|███████ | 42/60 [00:19<00:08, 2.18it/s]\n 72%|███████▏ | 43/60 [00:19<00:07, 2.18it/s]\n 73%|███████▎ | 44/60 [00:19<00:07, 2.18it/s]\n 75%|███████▌ | 45/60 [00:20<00:06, 2.18it/s]\n 77%|███████▋ | 46/60 [00:20<00:06, 2.18it/s]\n 78%|███████▊ | 47/60 [00:21<00:05, 2.18it/s]\n 80%|████████ | 48/60 [00:21<00:05, 2.18it/s]\n 82%|████████▏ | 49/60 [00:22<00:05, 2.18it/s]\n 83%|████████▎ | 50/60 [00:22<00:04, 2.18it/s]\n 85%|████████▌ | 51/60 [00:23<00:04, 2.18it/s]\n 87%|████████▋ | 52/60 [00:23<00:03, 2.18it/s]\n 88%|████████▊ | 53/60 [00:24<00:03, 2.18it/s]\n 90%|█████████ | 54/60 [00:24<00:02, 2.18it/s]\n 92%|█████████▏| 55/60 [00:25<00:02, 2.18it/s]\n 93%|█████████▎| 56/60 [00:25<00:01, 2.18it/s]\n 95%|█████████▌| 57/60 [00:25<00:01, 2.18it/s]\n 97%|█████████▋| 58/60 [00:26<00:00, 2.18it/s]\n 98%|█████████▊| 59/60 [00:26<00:00, 2.18it/s]\n100%|██████████| 60/60 [00:27<00:00, 2.18it/s]\n100%|██████████| 60/60 [00:27<00:00, 2.20it/s]",
"metrics": {
"predict_time": 29.411266516,
"total_time": 29.418155
},
"output": "https://replicate.delivery/xezq/8vezCUemUWog2UflzZoCUE4aLmpiVpuxO6s2ROJfAF9y6EOQB/output.mp4",
"started_at": "2025-01-09T23:53:51.403889Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-inlw63gsgk5pjmk6bmycoi3atdn7nu4rnfyerevduzpoqlo4mq4q",
"get": "https://api.replicate.com/v1/predictions/te08tpgr4nrm80cm9nyvkpz5n0",
"cancel": "https://api.replicate.com/v1/predictions/te08tpgr4nrm80cm9nyvkpz5n0/cancel"
},
"version": "807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189"
}Generated in
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