georgedavila / cog-ltx-video
Cog implementation of LTX video from its diffusers pipeline
Prediction
georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189ID11nzerh7qsrmc0cm9ngr0ys5pmStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- outFPS
- 24
- myprompt
- A bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.
- outWidth
- 768
- outHeight
- 512
- num_frames
- 97
- num_outputs
- 1
- guidanceScale
- 3
- num_inference_steps
- 60
{ "outFPS": 24, "myprompt": "A bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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 bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", outWidth: 768, outHeight: 512, num_frames: 97, num_outputs: 1, guidanceScale: 3, 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 replicateImport 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 bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 } ) print(output)To learn more, take a look at the guide on getting started with Python.
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 bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-09T23:23:49.789309Z", "created_at": "2025-01-09T23:23:20.382000Z", "data_removed": false, "error": null, "id": "11nzerh7qsrmc0cm9ngr0ys5pm", "input": { "outFPS": 24, "myprompt": "A bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 }, "logs": "Using seed: 2535\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, 2.88it/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, 2.31it/s]\n 10%|█ | 6/60 [00:02<00:23, 2.27it/s]\n 12%|█▏ | 7/60 [00:03<00:23, 2.24it/s]\n 13%|█▎ | 8/60 [00:03<00:23, 2.23it/s]\n 15%|█▌ | 9/60 [00:03<00:23, 2.21it/s]\n 17%|█▋ | 10/60 [00:04<00:22, 2.21it/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, 2.20it/s]\n 25%|██▌ | 15/60 [00:06<00:20, 2.20it/s]\n 27%|██▋ | 16/60 [00:07<00:20, 2.20it/s]\n 28%|██▊ | 17/60 [00:07<00:19, 2.20it/s]\n 30%|███ | 18/60 [00:08<00:19, 2.20it/s]\n 32%|███▏ | 19/60 [00:08<00:18, 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70%|███████ | 42/60 [00:18<00:08, 2.19it/s]\n 72%|███████▏ | 43/60 [00:19<00:07, 2.19it/s]\n 73%|███████▎ | 44/60 [00:19<00:07, 2.19it/s]\n 75%|███████▌ | 45/60 [00:20<00:06, 2.19it/s]\n 77%|███████▋ | 46/60 [00:20<00:06, 2.19it/s]\n 78%|███████▊ | 47/60 [00:21<00:05, 2.19it/s]\n 80%|████████ | 48/60 [00:21<00:05, 2.19it/s]\n 82%|████████▏ | 49/60 [00:22<00:05, 2.19it/s]\n 83%|████████▎ | 50/60 [00:22<00:04, 2.19it/s]\n 85%|████████▌ | 51/60 [00:23<00:04, 2.19it/s]\n 87%|████████▋ | 52/60 [00:23<00:03, 2.19it/s]\n 88%|████████▊ | 53/60 [00:24<00:03, 2.19it/s]\n 90%|█████████ | 54/60 [00:24<00:02, 2.19it/s]\n 92%|█████████▏| 55/60 [00:24<00:02, 2.19it/s]\n 93%|█████████▎| 56/60 [00:25<00:01, 2.19it/s]\n 95%|█████████▌| 57/60 [00:25<00:01, 2.19it/s]\n 97%|█████████▋| 58/60 [00:26<00:00, 2.19it/s]\n 98%|█████████▊| 59/60 [00:26<00:00, 2.19it/s]\n100%|██████████| 60/60 [00:27<00:00, 2.19it/s]\n100%|██████████| 60/60 [00:27<00:00, 2.21it/s]", "metrics": { "predict_time": 29.400612547, "total_time": 29.407309 }, "output": "https://replicate.delivery/xezq/ozSQ4zUD5d7DNd3zi23TGD2yeWf6ORd4cUtF7sxOtXGFygDUA/output.mp4", "started_at": "2025-01-09T23:23:20.388696Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-xhjdt33p42kjpwml7t6ro4ivl632sdure4xvkv7qcyp4kwcalunq", "get": "https://api.replicate.com/v1/predictions/11nzerh7qsrmc0cm9ngr0ys5pm", "cancel": "https://api.replicate.com/v1/predictions/11nzerh7qsrmc0cm9ngr0ys5pm/cancel" }, "version": "807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189" }Generated inUsing seed: 2535 0%| | 0/60 [00:00<?, ?it/s] 2%|▏ | 1/60 [00:00<00:26, 2.20it/s] 3%|▎ | 2/60 [00:00<00:20, 2.88it/s] 5%|▌ | 3/60 [00:01<00:22, 2.52it/s] 7%|▋ | 4/60 [00:01<00:23, 2.38it/s] 8%|▊ | 5/60 [00:02<00:23, 2.31it/s] 10%|█ | 6/60 [00:02<00:23, 2.27it/s] 12%|█▏ | 7/60 [00:03<00:23, 2.24it/s] 13%|█▎ | 8/60 [00:03<00:23, 2.23it/s] 15%|█▌ | 9/60 [00:03<00:23, 2.21it/s] 17%|█▋ | 10/60 [00:04<00:22, 2.21it/s] 18%|█▊ 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[00:25<00:01, 2.19it/s] 97%|█████████▋| 58/60 [00:26<00:00, 2.19it/s] 98%|█████████▊| 59/60 [00:26<00:00, 2.19it/s] 100%|██████████| 60/60 [00:27<00:00, 2.19it/s] 100%|██████████| 60/60 [00:27<00:00, 2.21it/s]Prediction
georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189IDx35dk1j6kxrmc0cm9nj8swcf24StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- outFPS
- 24
- myprompt
- A bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.
- outWidth
- 768
- outHeight
- 512
- num_frames
- 129
- num_outputs
- 1
- guidanceScale
- 1.1
- num_inference_steps
- 60
{ "outFPS": 24, "myprompt": "A bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", "outWidth": 768, "outHeight": 512, "num_frames": 129, "num_outputs": 1, "guidanceScale": 1.1, "num_inference_steps": 60 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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 bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", outWidth: 768, outHeight: 512, num_frames: 129, num_outputs: 1, guidanceScale: 1.1, 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 replicateImport 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 bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", "outWidth": 768, "outHeight": 512, "num_frames": 129, "num_outputs": 1, "guidanceScale": 1.1, "num_inference_steps": 60 } ) print(output)To learn more, take a look at the guide on getting started with Python.
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 bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", "outWidth": 768, "outHeight": 512, "num_frames": 129, "num_outputs": 1, "guidanceScale": 1.1, "num_inference_steps": 60 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-09T23:27:26.633183Z", "created_at": "2025-01-09T23:26:44.895000Z", "data_removed": false, "error": null, "id": "x35dk1j6kxrmc0cm9nj8swcf24", "input": { "outFPS": 24, "myprompt": "A bright orange lava river flows through an obsidian black canyon, cascading over a small waterfall and forming a pool of lava at the bottom. The lava river is the main focus of the scene, with fires shooting out at the surrounding trees and rocks. The canyon walls are steep and rocky, made of glassy black obsidian. The trees are mostly pine trees, with their green needles contrasting with the orange lava. The overall tone of the scene is one of doom and despair.", "outWidth": 768, "outHeight": 512, "num_frames": 129, "num_outputs": 1, "guidanceScale": 1.1, "num_inference_steps": 60 }, "logs": "Using seed: 42774\n 0%| | 0/60 [00:00<?, ?it/s]\n 2%|▏ | 1/60 [00:00<00:37, 1.55it/s]\n 3%|▎ | 2/60 [00:01<00:28, 2.03it/s]\n 5%|▌ | 3/60 [00:01<00:32, 1.78it/s]\n 7%|▋ | 4/60 [00:02<00:33, 1.68it/s]\n 8%|▊ | 5/60 [00:02<00:33, 1.63it/s]\n 10%|█ | 6/60 [00:03<00:33, 1.60it/s]\n 12%|█▏ | 7/60 [00:04<00:33, 1.58it/s]\n 13%|█▎ | 8/60 [00:04<00:33, 1.57it/s]\n 15%|█▌ | 9/60 [00:05<00:32, 1.56it/s]\n 17%|█▋ | 10/60 [00:06<00:32, 1.55it/s]\n 18%|█▊ | 11/60 [00:06<00:31, 1.55it/s]\n 20%|██ | 12/60 [00:07<00:31, 1.55it/s]\n 22%|██▏ | 13/60 [00:08<00:30, 1.55it/s]\n 23%|██▎ | 14/60 [00:08<00:29, 1.54it/s]\n 25%|██▌ | 15/60 [00:09<00:29, 1.54it/s]\n 27%|██▋ | 16/60 [00:10<00:28, 1.54it/s]\n 28%|██▊ | 17/60 [00:10<00:27, 1.54it/s]\n 30%|███ | 18/60 [00:11<00:27, 1.54it/s]\n 32%|███▏ | 19/60 [00:12<00:26, 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70%|███████ | 42/60 [00:26<00:11, 1.54it/s]\n 72%|███████▏ | 43/60 [00:27<00:11, 1.54it/s]\n 73%|███████▎ | 44/60 [00:28<00:10, 1.54it/s]\n 75%|███████▌ | 45/60 [00:28<00:09, 1.54it/s]\n 77%|███████▋ | 46/60 [00:29<00:09, 1.54it/s]\n 78%|███████▊ | 47/60 [00:30<00:08, 1.54it/s]\n 80%|████████ | 48/60 [00:30<00:07, 1.54it/s]\n 82%|████████▏ | 49/60 [00:31<00:07, 1.54it/s]\n 83%|████████▎ | 50/60 [00:32<00:06, 1.54it/s]\n 85%|████████▌ | 51/60 [00:32<00:05, 1.54it/s]\n 87%|████████▋ | 52/60 [00:33<00:05, 1.54it/s]\n 88%|████████▊ | 53/60 [00:34<00:04, 1.54it/s]\n 90%|█████████ | 54/60 [00:34<00:03, 1.54it/s]\n 92%|█████████▏| 55/60 [00:35<00:03, 1.54it/s]\n 93%|█████████▎| 56/60 [00:36<00:02, 1.54it/s]\n 95%|█████████▌| 57/60 [00:36<00:01, 1.54it/s]\n 97%|█████████▋| 58/60 [00:37<00:01, 1.54it/s]\n 98%|█████████▊| 59/60 [00:37<00:00, 1.54it/s]\n100%|██████████| 60/60 [00:38<00:00, 1.54it/s]\n100%|██████████| 60/60 [00:38<00:00, 1.55it/s]", "metrics": { "predict_time": 41.731844015, "total_time": 41.738183 }, "output": "https://replicate.delivery/xezq/IVgB7cFANYaBGtffZmyfPt3K4BN9eAf4sBJrIRAdciW3rGcgC/output.mp4", "started_at": "2025-01-09T23:26:44.901339Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-mxxn4tlzzevn3ywk5fnhnztux3kfoxjqgsxhqbvk2d6bk4ale6ha", "get": "https://api.replicate.com/v1/predictions/x35dk1j6kxrmc0cm9nj8swcf24", "cancel": "https://api.replicate.com/v1/predictions/x35dk1j6kxrmc0cm9nj8swcf24/cancel" }, "version": "807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189" }Generated inUsing seed: 42774 0%| | 0/60 [00:00<?, ?it/s] 2%|▏ | 1/60 [00:00<00:37, 1.55it/s] 3%|▎ | 2/60 [00:01<00:28, 2.03it/s] 5%|▌ | 3/60 [00:01<00:32, 1.78it/s] 7%|▋ | 4/60 [00:02<00:33, 1.68it/s] 8%|▊ | 5/60 [00:02<00:33, 1.63it/s] 10%|█ | 6/60 [00:03<00:33, 1.60it/s] 12%|█▏ | 7/60 [00:04<00:33, 1.58it/s] 13%|█▎ | 8/60 [00:04<00:33, 1.57it/s] 15%|█▌ | 9/60 [00:05<00:32, 1.56it/s] 17%|█▋ | 10/60 [00:06<00:32, 1.55it/s] 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[00:36<00:01, 1.54it/s] 97%|█████████▋| 58/60 [00:37<00:01, 1.54it/s] 98%|█████████▊| 59/60 [00:37<00:00, 1.54it/s] 100%|██████████| 60/60 [00:38<00:00, 1.54it/s] 100%|██████████| 60/60 [00:38<00:00, 1.55it/s]Prediction
georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189ID4vrw8nq8edrm80cm9nmrgcq7rmStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- outFPS
- 24
- myprompt
- A woman walks away from a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, walks away from the red convertible parked on the left side of the street, her back to the camera; she walks at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she walks up a set of stairs towards a building with a green door; the scene is captured in real-life footage.
- outWidth
- 768
- outHeight
- 512
- num_frames
- 97
- num_outputs
- 1
- guidanceScale
- 3
- num_inference_steps
- 60
{ "outFPS": 24, "myprompt": "A woman walks away from a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, walks away from the red convertible parked on the left side of the street, her back to the camera; she walks at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she walks up a set of stairs towards a building with a green door; the scene is captured in real-life footage.", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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 walks away from a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, walks away from the red convertible parked on the left side of the street, her back to the camera; she walks at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she walks up a set of stairs towards a building with a green door; the scene is captured in real-life footage.", outWidth: 768, outHeight: 512, num_frames: 97, num_outputs: 1, guidanceScale: 3, 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 replicateImport 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 walks away from a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, walks away from the red convertible parked on the left side of the street, her back to the camera; she walks at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she walks up a set of stairs towards a building with a green door; the scene is captured in real-life footage.", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 } ) print(output)To learn more, take a look at the guide on getting started with Python.
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 walks away from a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, walks away from the red convertible parked on the left side of the street, her back to the camera; she walks at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she walks up a set of stairs towards a building with a green door; the scene is captured in real-life footage.", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-09T23:33:23.514808Z", "created_at": "2025-01-09T23:32:54.003000Z", "data_removed": false, "error": null, "id": "4vrw8nq8edrm80cm9nmrgcq7rm", "input": { "outFPS": 24, "myprompt": "A woman walks away from a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, walks away from the red convertible parked on the left side of the street, her back to the camera; she walks at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she walks up a set of stairs towards a building with a green door; the scene is captured in real-life footage.", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 }, "logs": "Using seed: 36791\n 0%| | 0/60 [00:00<?, ?it/s]\n 2%|▏ | 1/60 [00:00<00:26, 2.21it/s]\n 3%|▎ | 2/60 [00:00<00:20, 2.89it/s]\n 5%|▌ | 3/60 [00:01<00:22, 2.53it/s]\n 7%|▋ | 4/60 [00:01<00:23, 2.39it/s]\n 8%|▊ | 5/60 [00:02<00:23, 2.32it/s]\n 10%|█ | 6/60 [00:02<00:23, 2.28it/s]\n 12%|█▏ | 7/60 [00:02<00:23, 2.25it/s]\n 13%|█▎ | 8/60 [00:03<00:23, 2.23it/s]\n 15%|█▌ | 9/60 [00:03<00:22, 2.22it/s]\n 17%|█▋ | 10/60 [00:04<00:22, 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92%|█████████▏| 55/60 [00:24<00:02, 2.19it/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": 29.505194716, "total_time": 29.511808 }, "output": "https://replicate.delivery/xezq/cNtxFAKwCNqCPdIMENoqpspxhuvquPWUCfeBFfppgfuPsDOQB/output.mp4", "started_at": "2025-01-09T23:32:54.009613Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-yte2bvigfplq56dtrmxuehqxjkpjw6fq24uwhyroac4thh6z22cq", "get": "https://api.replicate.com/v1/predictions/4vrw8nq8edrm80cm9nmrgcq7rm", "cancel": "https://api.replicate.com/v1/predictions/4vrw8nq8edrm80cm9nmrgcq7rm/cancel" }, "version": "807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189" }Generated inUsing seed: 36791 0%| | 0/60 [00:00<?, 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georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189IDk7293th9tdrm80cm9nrsh0k7egStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- outFPS
- 24
- myprompt
- A woman jumps over a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, jumps over the red convertible parked on the left side of the street, her back to the camera; she moves at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she jumps over the red convertible; the scene is captured in real-life footage.
- outWidth
- 512
- outHeight
- 512
- num_frames
- 97
- num_outputs
- 1
- guidanceScale
- 3
- num_inference_steps
- 60
{ "outFPS": 24, "myprompt": "A woman jumps over a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, jumps over the red convertible parked on the left side of the street, her back to the camera; she moves at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she jumps over the red convertible; the scene is captured in real-life footage.", "outWidth": 512, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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 jumps over a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, jumps over the red convertible parked on the left side of the street, her back to the camera; she moves at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she jumps over the red convertible; the scene is captured in real-life footage.", outWidth: 512, outHeight: 512, num_frames: 97, num_outputs: 1, guidanceScale: 3, 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 replicateImport 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 jumps over a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, jumps over the red convertible parked on the left side of the street, her back to the camera; she moves at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she jumps over the red convertible; the scene is captured in real-life footage.", "outWidth": 512, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 } ) print(output)To learn more, take a look at the guide on getting started with Python.
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 jumps over a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, jumps over the red convertible parked on the left side of the street, her back to the camera; she moves at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she jumps over the red convertible; the scene is captured in real-life footage.", "outWidth": 512, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-09T23:41:05.715090Z", "created_at": "2025-01-09T23:40:49.491000Z", "data_removed": false, "error": null, "id": "k7293th9tdrm80cm9nrsh0k7eg", "input": { "outFPS": 24, "myprompt": "A woman jumps over a red convertible parked on a city street during daytime. The woman, wearing a dark jacket and jeans, jumps over the red convertible parked on the left side of the street, her back to the camera; she moves at a steady pace, her arms swinging slightly by her sides; the street is well lit, with the sun casting light on the wet pavement; the camera follows the woman from behind as she jumps over the red convertible; the scene is captured in real-life footage.", "outWidth": 512, "outHeight": 512, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "num_inference_steps": 60 }, "logs": "Using seed: 45731\n 0%| | 0/60 [00:00<?, ?it/s]\n 2%|▏ | 1/60 [00:00<00:14, 4.10it/s]\n 3%|▎ | 2/60 [00:00<00:10, 5.35it/s]\n 5%|▌ | 3/60 [00:00<00:12, 4.68it/s]\n 7%|▋ | 4/60 [00:00<00:12, 4.42it/s]\n 8%|▊ | 5/60 [00:01<00:12, 4.28it/s]\n 10%|█ | 6/60 [00:01<00:12, 4.21it/s]\n 12%|█▏ | 7/60 [00:01<00:12, 4.17it/s]\n 13%|█▎ | 8/60 [00:01<00:12, 4.14it/s]\n 15%|█▌ | 9/60 [00:02<00:12, 4.12it/s]\n 17%|█▋ | 10/60 [00:02<00:12, 4.11it/s]\n 18%|█▊ | 11/60 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4.06it/s]\n 93%|█████████▎| 56/60 [00:13<00:00, 4.05it/s]\n 95%|█████████▌| 57/60 [00:13<00:00, 4.05it/s]\n 97%|█████████▋| 58/60 [00:14<00:00, 4.05it/s]\n 98%|█████████▊| 59/60 [00:14<00:00, 4.05it/s]\n100%|██████████| 60/60 [00:14<00:00, 4.05it/s]\n100%|██████████| 60/60 [00:14<00:00, 4.09it/s]", "metrics": { "predict_time": 16.216439056, "total_time": 16.22409 }, "output": "https://replicate.delivery/xezq/JBLdfZS9ruxmb6zi8nRPlyf5UhjdvJjwoennFA0CqEFjECHoA/output.mp4", "started_at": "2025-01-09T23:40:49.498651Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-asywqjhghqzoybaeub5tafysxpbaajp6njjrky7mcbkb3tdkc3ha", "get": "https://api.replicate.com/v1/predictions/k7293th9tdrm80cm9nrsh0k7eg", "cancel": "https://api.replicate.com/v1/predictions/k7293th9tdrm80cm9nrsh0k7eg/cancel" }, "version": "807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189" }Generated inUsing seed: 45731 0%| | 0/60 [00:00<?, ?it/s] 2%|▏ | 1/60 [00:00<00:14, 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4.06it/s] 83%|████████▎ | 50/60 [00:12<00:02, 4.05it/s] 85%|████████▌ | 51/60 [00:12<00:02, 4.05it/s] 87%|████████▋ | 52/60 [00:12<00:01, 4.05it/s] 88%|████████▊ | 53/60 [00:12<00:01, 4.05it/s] 90%|█████████ | 54/60 [00:13<00:01, 4.05it/s] 92%|█████████▏| 55/60 [00:13<00:01, 4.06it/s] 93%|█████████▎| 56/60 [00:13<00:00, 4.05it/s] 95%|█████████▌| 57/60 [00:13<00:00, 4.05it/s] 97%|█████████▋| 58/60 [00:14<00:00, 4.05it/s] 98%|█████████▊| 59/60 [00:14<00:00, 4.05it/s] 100%|██████████| 60/60 [00:14<00:00, 4.05it/s] 100%|██████████| 60/60 [00:14<00:00, 4.09it/s]Prediction
georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189IDy5bvzj93hxrme0cm9ny9wctp14StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- outFPS
- 24
- myprompt
- The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage.
- outWidth
- 736
- outHeight
- 480
- num_frames
- 97
- num_outputs
- 1
- guidanceScale
- 3
- negative_prompt
- bad quality
- num_inference_steps
- 60
{ "outFPS": 24, "myprompt": "The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. ", "outWidth": 736, "outHeight": 480, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "negative_prompt": "bad quality", "num_inference_steps": 60 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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: "The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. ", outWidth: 736, outHeight: 480, num_frames: 97, num_outputs: 1, guidanceScale: 3, negative_prompt: "bad quality", 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 replicateImport 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": "The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. ", "outWidth": 736, "outHeight": 480, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "negative_prompt": "bad quality", "num_inference_steps": 60 } ) print(output)To learn more, take a look at the guide on getting started with Python.
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": "The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. ", "outWidth": 736, "outHeight": 480, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "negative_prompt": "bad quality", "num_inference_steps": 60 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-09T23:53:13.750046Z", "created_at": "2025-01-09T23:52:48.783000Z", "data_removed": false, "error": null, "id": "y5bvzj93hxrme0cm9ny9wctp14", "input": { "outFPS": 24, "myprompt": "The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. The Grand Canyon filled with pink cotton candy, photorealistic aerial footage. ", "outWidth": 736, "outHeight": 480, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "negative_prompt": "bad quality", "num_inference_steps": 60 }, "logs": "Using seed: 28431\n 0%| | 0/60 [00:00<?, ?it/s]\n 2%|▏ | 1/60 [00:00<00:22, 2.61it/s]\n 3%|▎ | 2/60 [00:00<00:16, 3.42it/s]\n 5%|▌ | 3/60 [00:00<00:19, 2.99it/s]\n 7%|▋ | 4/60 [00:01<00:19, 2.82it/s]\n 8%|▊ | 5/60 [00:01<00:20, 2.74it/s]\n 10%|█ | 6/60 [00:02<00:20, 2.69it/s]\n 12%|█▏ | 7/60 [00:02<00:19, 2.66it/s]\n 13%|█▎ | 8/60 [00:02<00:19, 2.64it/s]\n 15%|█▌ | 9/60 [00:03<00:19, 2.62it/s]\n 17%|█▋ | 10/60 [00:03<00:19, 2.61it/s]\n 18%|█▊ | 11/60 [00:04<00:18, 2.61it/s]\n 20%|██ | 12/60 [00:04<00:18, 2.60it/s]\n 22%|██▏ | 13/60 [00:04<00:18, 2.60it/s]\n 23%|██▎ | 14/60 [00:05<00:17, 2.60it/s]\n 25%|██▌ | 15/60 [00:05<00:17, 2.60it/s]\n 27%|██▋ | 16/60 [00:06<00:16, 2.60it/s]\n 28%|██▊ | 17/60 [00:06<00:16, 2.60it/s]\n 30%|███ | 18/60 [00:06<00:16, 2.60it/s]\n 32%|███▏ | 19/60 [00:07<00:15, 2.60it/s]\n 33%|███▎ | 20/60 [00:07<00:15, 2.60it/s]\n 35%|███▌ | 21/60 [00:07<00:15, 2.60it/s]\n 37%|███▋ | 22/60 [00:08<00:14, 2.60it/s]\n 38%|███▊ | 23/60 [00:08<00:14, 2.60it/s]\n 40%|████ | 24/60 [00:09<00:13, 2.60it/s]\n 42%|████▏ | 25/60 [00:09<00:13, 2.60it/s]\n 43%|████▎ | 26/60 [00:09<00:13, 2.59it/s]\n 45%|████▌ | 27/60 [00:10<00:12, 2.59it/s]\n 47%|████▋ | 28/60 [00:10<00:12, 2.59it/s]\n 48%|████▊ | 29/60 [00:11<00:11, 2.59it/s]\n 50%|█████ | 30/60 [00:11<00:11, 2.59it/s]\n 52%|█████▏ | 31/60 [00:11<00:11, 2.59it/s]\n 53%|█████▎ | 32/60 [00:12<00:10, 2.59it/s]\n 55%|█████▌ | 33/60 [00:12<00:10, 2.59it/s]\n 57%|█████▋ | 34/60 [00:12<00:10, 2.59it/s]\n 58%|█████▊ | 35/60 [00:13<00:09, 2.59it/s]\n 60%|██████ | 36/60 [00:13<00:09, 2.59it/s]\n 62%|██████▏ | 37/60 [00:14<00:08, 2.59it/s]\n 63%|██████▎ | 38/60 [00:14<00:08, 2.59it/s]\n 65%|██████▌ | 39/60 [00:14<00:08, 2.59it/s]\n 67%|██████▋ | 40/60 [00:15<00:07, 2.59it/s]\n 68%|██████▊ | 41/60 [00:15<00:07, 2.59it/s]\n 70%|███████ | 42/60 [00:16<00:06, 2.59it/s]\n 72%|███████▏ | 43/60 [00:16<00:06, 2.59it/s]\n 73%|███████▎ | 44/60 [00:16<00:06, 2.59it/s]\n 75%|███████▌ | 45/60 [00:17<00:05, 2.59it/s]\n 77%|███████▋ | 46/60 [00:17<00:05, 2.59it/s]\n 78%|███████▊ | 47/60 [00:17<00:05, 2.59it/s]\n 80%|████████ | 48/60 [00:18<00:04, 2.59it/s]\n 82%|████████▏ | 49/60 [00:18<00:04, 2.59it/s]\n 83%|████████▎ | 50/60 [00:19<00:03, 2.59it/s]\n 85%|████████▌ | 51/60 [00:19<00:03, 2.59it/s]\n 87%|████████▋ | 52/60 [00:19<00:03, 2.59it/s]\n 88%|████████▊ | 53/60 [00:20<00:02, 2.58it/s]\n 90%|█████████ | 54/60 [00:20<00:02, 2.58it/s]\n 92%|█████████▏| 55/60 [00:21<00:01, 2.58it/s]\n 93%|█████████▎| 56/60 [00:21<00:01, 2.58it/s]\n 95%|█████████▌| 57/60 [00:21<00:01, 2.58it/s]\n 97%|█████████▋| 58/60 [00:22<00:00, 2.58it/s]\n 98%|█████████▊| 59/60 [00:22<00:00, 2.58it/s]\n100%|██████████| 60/60 [00:23<00:00, 2.58it/s]\n100%|██████████| 60/60 [00:23<00:00, 2.61it/s]", "metrics": { "predict_time": 24.95974621, "total_time": 24.967046 }, "output": "https://replicate.delivery/xezq/2SSoD5DI2PY6LVe1kFweQS0CaKVBf205O8hV7puhzgySbCHoA/output.mp4", "started_at": "2025-01-09T23:52:48.790300Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-3ed2fan4rgujylz5gw5cdoqxvqov37sbrrprpg3tm5s26ixrpxzq", "get": "https://api.replicate.com/v1/predictions/y5bvzj93hxrme0cm9ny9wctp14", "cancel": "https://api.replicate.com/v1/predictions/y5bvzj93hxrme0cm9ny9wctp14/cancel" }, "version": "807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189" }Generated inUsing seed: 28431 0%| | 0/60 [00:00<?, ?it/s] 2%|▏ | 1/60 [00:00<00:22, 2.61it/s] 3%|▎ | 2/60 [00:00<00:16, 3.42it/s] 5%|▌ | 3/60 [00:00<00:19, 2.99it/s] 7%|▋ | 4/60 [00:01<00:19, 2.82it/s] 8%|▊ | 5/60 [00:01<00:20, 2.74it/s] 10%|█ | 6/60 [00:02<00:20, 2.69it/s] 12%|█▏ | 7/60 [00:02<00:19, 2.66it/s] 13%|█▎ | 8/60 [00:02<00:19, 2.64it/s] 15%|█▌ | 9/60 [00:03<00:19, 2.62it/s] 17%|█▋ | 10/60 [00:03<00:19, 2.61it/s] 18%|█▊ | 11/60 [00:04<00:18, 2.61it/s] 20%|██ | 12/60 [00:04<00:18, 2.60it/s] 22%|██▏ | 13/60 [00:04<00:18, 2.60it/s] 23%|██▎ | 14/60 [00:05<00:17, 2.60it/s] 25%|██▌ | 15/60 [00:05<00:17, 2.60it/s] 27%|██▋ | 16/60 [00:06<00:16, 2.60it/s] 28%|██▊ | 17/60 [00:06<00:16, 2.60it/s] 30%|███ | 18/60 [00:06<00:16, 2.60it/s] 32%|███▏ | 19/60 [00:07<00:15, 2.60it/s] 33%|███▎ | 20/60 [00:07<00:15, 2.60it/s] 35%|███▌ | 21/60 [00:07<00:15, 2.60it/s] 37%|███▋ | 22/60 [00:08<00:14, 2.60it/s] 38%|███▊ | 23/60 [00:08<00:14, 2.60it/s] 40%|████ | 24/60 [00:09<00:13, 2.60it/s] 42%|████▏ | 25/60 [00:09<00:13, 2.60it/s] 43%|████▎ | 26/60 [00:09<00:13, 2.59it/s] 45%|████▌ | 27/60 [00:10<00:12, 2.59it/s] 47%|████▋ | 28/60 [00:10<00:12, 2.59it/s] 48%|████▊ | 29/60 [00:11<00:11, 2.59it/s] 50%|█████ | 30/60 [00:11<00:11, 2.59it/s] 52%|█████▏ | 31/60 [00:11<00:11, 2.59it/s] 53%|█████▎ | 32/60 [00:12<00:10, 2.59it/s] 55%|█████▌ | 33/60 [00:12<00:10, 2.59it/s] 57%|█████▋ | 34/60 [00:12<00:10, 2.59it/s] 58%|█████▊ | 35/60 [00:13<00:09, 2.59it/s] 60%|██████ | 36/60 [00:13<00:09, 2.59it/s] 62%|██████▏ | 37/60 [00:14<00:08, 2.59it/s] 63%|██████▎ | 38/60 [00:14<00:08, 2.59it/s] 65%|██████▌ | 39/60 [00:14<00:08, 2.59it/s] 67%|██████▋ | 40/60 [00:15<00:07, 2.59it/s] 68%|██████▊ | 41/60 [00:15<00:07, 2.59it/s] 70%|███████ | 42/60 [00:16<00:06, 2.59it/s] 72%|███████▏ | 43/60 [00:16<00:06, 2.59it/s] 73%|███████▎ | 44/60 [00:16<00:06, 2.59it/s] 75%|███████▌ | 45/60 [00:17<00:05, 2.59it/s] 77%|███████▋ | 46/60 [00:17<00:05, 2.59it/s] 78%|███████▊ | 47/60 [00:17<00:05, 2.59it/s] 80%|████████ | 48/60 [00:18<00:04, 2.59it/s] 82%|████████▏ | 49/60 [00:18<00:04, 2.59it/s] 83%|████████▎ | 50/60 [00:19<00:03, 2.59it/s] 85%|████████▌ | 51/60 [00:19<00:03, 2.59it/s] 87%|████████▋ | 52/60 [00:19<00:03, 2.59it/s] 88%|████████▊ | 53/60 [00:20<00:02, 2.58it/s] 90%|█████████ | 54/60 [00:20<00:02, 2.58it/s] 92%|█████████▏| 55/60 [00:21<00:01, 2.58it/s] 93%|█████████▎| 56/60 [00:21<00:01, 2.58it/s] 95%|█████████▌| 57/60 [00:21<00:01, 2.58it/s] 97%|█████████▋| 58/60 [00:22<00:00, 2.58it/s] 98%|█████████▊| 59/60 [00:22<00:00, 2.58it/s] 100%|██████████| 60/60 [00:23<00:00, 2.58it/s] 100%|██████████| 60/60 [00:23<00:00, 2.61it/s]Prediction
georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189IDte08tpgr4nrm80cm9nyvkpz5n0StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- 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
{ "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 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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 replicateImport 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.
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.
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 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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 inUsing seed: 12353 0%| | 0/60 [00:00<?, ?it/s] 2%|▏ | 1/60 [00:00<00:26, 2.20it/s] 3%|▎ | 2/60 [00:00<00:20, 2.87it/s] 5%|▌ | 3/60 [00:01<00:22, 2.52it/s] 7%|▋ | 4/60 [00:01<00:23, 2.38it/s] 8%|▊ | 5/60 [00:02<00:23, 2.30it/s] 10%|█ | 6/60 [00:02<00:23, 2.26it/s] 12%|█▏ | 7/60 [00:03<00:23, 2.24it/s] 13%|█▎ | 8/60 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2.18it/s] 55%|█████▌ | 33/60 [00:14<00:12, 2.18it/s] 57%|█████▋ | 34/60 [00:15<00:11, 2.18it/s] 58%|█████▊ | 35/60 [00:15<00:11, 2.18it/s] 60%|██████ | 36/60 [00:16<00:11, 2.18it/s] 62%|██████▏ | 37/60 [00:16<00:10, 2.18it/s] 63%|██████▎ | 38/60 [00:17<00:10, 2.18it/s] 65%|██████▌ | 39/60 [00:17<00:09, 2.18it/s] 67%|██████▋ | 40/60 [00:18<00:09, 2.18it/s] 68%|██████▊ | 41/60 [00:18<00:08, 2.18it/s] 70%|███████ | 42/60 [00:19<00:08, 2.18it/s] 72%|███████▏ | 43/60 [00:19<00:07, 2.18it/s] 73%|███████▎ | 44/60 [00:19<00:07, 2.18it/s] 75%|███████▌ | 45/60 [00:20<00:06, 2.18it/s] 77%|███████▋ | 46/60 [00:20<00:06, 2.18it/s] 78%|███████▊ | 47/60 [00:21<00:05, 2.18it/s] 80%|████████ | 48/60 [00:21<00:05, 2.18it/s] 82%|████████▏ | 49/60 [00:22<00:05, 2.18it/s] 83%|████████▎ | 50/60 [00:22<00:04, 2.18it/s] 85%|████████▌ | 51/60 [00:23<00:04, 2.18it/s] 87%|████████▋ | 52/60 [00:23<00:03, 2.18it/s] 88%|████████▊ | 53/60 [00:24<00:03, 2.18it/s] 90%|█████████ | 54/60 [00:24<00:02, 2.18it/s] 92%|█████████▏| 55/60 [00:25<00:02, 2.18it/s] 93%|█████████▎| 56/60 [00:25<00:01, 2.18it/s] 95%|█████████▌| 57/60 [00:25<00:01, 2.18it/s] 97%|█████████▋| 58/60 [00:26<00:00, 2.18it/s] 98%|█████████▊| 59/60 [00:26<00:00, 2.18it/s] 100%|██████████| 60/60 [00:27<00:00, 2.18it/s] 100%|██████████| 60/60 [00:27<00:00, 2.20it/s]Prediction
georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189IDpc5e63199nrma0cm9p1tjdyg2rStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- outFPS
- 24
- myprompt
- A robot cyborg woman with a shiny metal face and metal facial features smiles at another woman with long blonde hair. The robot cyborg woman with brown hair wears a black jacket and has a metal face. The camera angle is a close-up, focused on the robot cyborg woman's metal 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
- num_inference_steps
- 60
{ "outFPS": 24, "myprompt": "A robot cyborg woman with a shiny metal face and metal facial features smiles at another woman with long blonde hair. The robot cyborg woman with brown hair wears a black jacket and has a metal face. The camera angle is a close-up, focused on the robot cyborg woman's metal 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, "num_inference_steps": 60 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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 robot cyborg woman with a shiny metal face and metal facial features smiles at another woman with long blonde hair. The robot cyborg woman with brown hair wears a black jacket and has a metal face. The camera angle is a close-up, focused on the robot cyborg woman's metal 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, 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 replicateImport 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 robot cyborg woman with a shiny metal face and metal facial features smiles at another woman with long blonde hair. The robot cyborg woman with brown hair wears a black jacket and has a metal face. The camera angle is a close-up, focused on the robot cyborg woman's metal 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, "num_inference_steps": 60 } ) print(output)To learn more, take a look at the guide on getting started with Python.
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 robot cyborg woman with a shiny metal face and metal facial features smiles at another woman with long blonde hair. The robot cyborg woman with brown hair wears a black jacket and has a metal face. The camera angle is a close-up, focused on the robot cyborg woman\'s metal 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, "num_inference_steps": 60 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-10T00:00:58.896975Z", "created_at": "2025-01-10T00:00:29.005000Z", "data_removed": false, "error": null, "id": "pc5e63199nrma0cm9p1tjdyg2r", "input": { "outFPS": 24, "myprompt": "A robot cyborg woman with a shiny metal face and metal facial features smiles at another woman with long blonde hair. The robot cyborg woman with brown hair wears a black jacket and has a metal face. The camera angle is a close-up, focused on the robot cyborg woman's metal 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, "num_inference_steps": 60 }, "logs": "Using seed: 29767\n 0%| | 0/60 [00:00<?, ?it/s]\n 2%|▏ | 1/60 [00:00<00:26, 2.19it/s]\n 3%|▎ | 2/60 [00:00<00:20, 2.86it/s]\n 5%|▌ | 3/60 [00:01<00:22, 2.51it/s]\n 7%|▋ | 4/60 [00:01<00:23, 2.37it/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, 2.23it/s]\n 13%|█▎ | 8/60 [00:03<00:23, 2.21it/s]\n 15%|█▌ | 9/60 [00:03<00:23, 2.20it/s]\n 17%|█▋ | 10/60 [00:04<00:22, 2.19it/s]\n 18%|█▊ | 11/60 [00:04<00:22, 2.19it/s]\n 20%|██ | 12/60 [00:05<00:21, 2.18it/s]\n 22%|██▏ | 13/60 [00:05<00:21, 2.18it/s]\n 23%|██▎ | 14/60 [00:06<00:21, 2.18it/s]\n 25%|██▌ | 15/60 [00:06<00:20, 2.18it/s]\n 27%|██▋ | 16/60 [00:07<00:20, 2.18it/s]\n 28%|██▊ | 17/60 [00:07<00:19, 2.17it/s]\n 30%|███ | 18/60 [00:08<00:19, 2.17it/s]\n 32%|███▏ | 19/60 [00:08<00:18, 2.17it/s]\n 33%|███▎ 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[00:19<00:08, 2.18it/s]\n 72%|███████▏ | 43/60 [00:19<00:07, 2.18it/s]\n 73%|███████▎ | 44/60 [00:20<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, 2.19it/s]", "metrics": { "predict_time": 29.884422397, "total_time": 29.891975 }, "output": "https://replicate.delivery/xezq/7yeJZHfjgQrOkE5n7FuC3f3CCNqK9e8ue2QKNiXOEVIUnKcgC/output.mp4", "started_at": "2025-01-10T00:00:29.012552Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-nutteoxmzz4hy66boaargnrocejn6gpm5qkyv7n6ix7a3x6bvexq", "get": "https://api.replicate.com/v1/predictions/pc5e63199nrma0cm9p1tjdyg2r", "cancel": "https://api.replicate.com/v1/predictions/pc5e63199nrma0cm9p1tjdyg2r/cancel" }, "version": "807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189" }Generated inUsing seed: 29767 0%| | 0/60 [00:00<?, ?it/s] 2%|▏ | 1/60 [00:00<00:26, 2.19it/s] 3%|▎ | 2/60 [00:00<00:20, 2.86it/s] 5%|▌ | 3/60 [00:01<00:22, 2.51it/s] 7%|▋ | 4/60 [00:01<00:23, 2.37it/s] 8%|▊ | 5/60 [00:02<00:23, 2.30it/s] 10%|█ | 6/60 [00:02<00:23, 2.26it/s] 12%|█▏ | 7/60 [00:03<00:23, 2.23it/s] 13%|█▎ | 8/60 [00:03<00:23, 2.21it/s] 15%|█▌ | 9/60 [00:03<00:23, 2.20it/s] 17%|█▋ | 10/60 [00:04<00:22, 2.19it/s] 18%|█▊ | 11/60 [00:04<00:22, 2.19it/s] 20%|██ | 12/60 [00:05<00:21, 2.18it/s] 22%|██▏ | 13/60 [00:05<00:21, 2.18it/s] 23%|██▎ | 14/60 [00:06<00:21, 2.18it/s] 25%|██▌ | 15/60 [00:06<00:20, 2.18it/s] 27%|██▋ | 16/60 [00:07<00:20, 2.18it/s] 28%|██▊ | 17/60 [00:07<00:19, 2.17it/s] 30%|███ | 18/60 [00:08<00:19, 2.17it/s] 32%|███▏ | 19/60 [00:08<00:18, 2.17it/s] 33%|███▎ | 20/60 [00:09<00:18, 2.17it/s] 35%|███▌ | 21/60 [00:09<00:17, 2.17it/s] 37%|███▋ | 22/60 [00:09<00:17, 2.17it/s] 38%|███▊ | 23/60 [00:10<00:17, 2.17it/s] 40%|████ | 24/60 [00:10<00:16, 2.17it/s] 42%|████▏ | 25/60 [00:11<00:16, 2.18it/s] 43%|████▎ | 26/60 [00:11<00:15, 2.18it/s] 45%|████▌ | 27/60 [00:12<00:15, 2.18it/s] 47%|████▋ | 28/60 [00:12<00:14, 2.18it/s] 48%|████▊ | 29/60 [00:13<00:14, 2.18it/s] 50%|█████ | 30/60 [00:13<00:13, 2.18it/s] 52%|█████▏ | 31/60 [00:14<00:13, 2.18it/s] 53%|█████▎ | 32/60 [00:14<00:12, 2.18it/s] 55%|█████▌ | 33/60 [00:14<00:12, 2.18it/s] 57%|█████▋ | 34/60 [00:15<00:11, 2.18it/s] 58%|█████▊ | 35/60 [00:15<00:11, 2.18it/s] 60%|██████ | 36/60 [00:16<00:11, 2.18it/s] 62%|██████▏ | 37/60 [00:16<00:10, 2.18it/s] 63%|██████▎ | 38/60 [00:17<00:10, 2.18it/s] 65%|██████▌ | 39/60 [00:17<00:09, 2.18it/s] 67%|██████▋ | 40/60 [00:18<00:09, 2.18it/s] 68%|██████▊ | 41/60 [00:18<00:08, 2.18it/s] 70%|███████ | 42/60 [00:19<00:08, 2.18it/s] 72%|███████▏ | 43/60 [00:19<00:07, 2.18it/s] 73%|███████▎ | 44/60 [00:20<00:07, 2.18it/s] 75%|███████▌ | 45/60 [00:20<00:06, 2.18it/s] 77%|███████▋ | 46/60 [00:20<00:06, 2.18it/s] 78%|███████▊ | 47/60 [00:21<00:05, 2.18it/s] 80%|████████ | 48/60 [00:21<00:05, 2.18it/s] 82%|████████▏ | 49/60 [00:22<00:05, 2.18it/s] 83%|████████▎ | 50/60 [00:22<00:04, 2.18it/s] 85%|████████▌ | 51/60 [00:23<00:04, 2.18it/s] 87%|████████▋ | 52/60 [00:23<00:03, 2.18it/s] 88%|████████▊ | 53/60 [00:24<00:03, 2.18it/s] 90%|█████████ | 54/60 [00:24<00:02, 2.18it/s] 92%|█████████▏| 55/60 [00:25<00:02, 2.18it/s] 93%|█████████▎| 56/60 [00:25<00:01, 2.18it/s] 95%|█████████▌| 57/60 [00:25<00:01, 2.18it/s] 97%|█████████▋| 58/60 [00:26<00:00, 2.18it/s] 98%|█████████▊| 59/60 [00:26<00:00, 2.18it/s] 100%|██████████| 60/60 [00:27<00:00, 2.18it/s] 100%|██████████| 60/60 [00:27<00:00, 2.19it/s]Prediction
georgedavila/cog-ltx-video:807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189IDgtnc7qk2b5rma0cm9p6ba4vsy0StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- outFPS
- 24
- myprompt
- A chef prepares food in a professional kitchen. He has olive skin and dark, close-cropped hair, wearing traditional white chef's attire. Steam rises from the pan he's working with. The kitchen's stainless steel surfaces reflect the bright overhead lighting. The camera follows his hands as he cooks. The scene appears to be real-life footage.
- outWidth
- 864
- outHeight
- 480
- num_frames
- 97
- num_outputs
- 1
- guidanceScale
- 3
- negative_prompt
- low quality, worst quality, deformed, distorted, watermark
- num_inference_steps
- 30
{ "outFPS": 24, "myprompt": "A chef prepares food in a professional kitchen. He has olive skin and dark, close-cropped hair, wearing traditional white chef's attire. Steam rises from the pan he's working with. The kitchen's stainless steel surfaces reflect the bright overhead lighting. The camera follows his hands as he cooks. The scene appears to be real-life footage.", "outWidth": 864, "outHeight": 480, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "negative_prompt": "low quality, worst quality, deformed, distorted, watermark", "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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 chef prepares food in a professional kitchen. He has olive skin and dark, close-cropped hair, wearing traditional white chef's attire. Steam rises from the pan he's working with. The kitchen's stainless steel surfaces reflect the bright overhead lighting. The camera follows his hands as he cooks. The scene appears to be real-life footage.", outWidth: 864, outHeight: 480, num_frames: 97, num_outputs: 1, guidanceScale: 3, negative_prompt: "low quality, worst quality, deformed, distorted, watermark", num_inference_steps: 30 } } ); // 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 replicateImport 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 chef prepares food in a professional kitchen. He has olive skin and dark, close-cropped hair, wearing traditional white chef's attire. Steam rises from the pan he's working with. The kitchen's stainless steel surfaces reflect the bright overhead lighting. The camera follows his hands as he cooks. The scene appears to be real-life footage.", "outWidth": 864, "outHeight": 480, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "negative_prompt": "low quality, worst quality, deformed, distorted, watermark", "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
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 chef prepares food in a professional kitchen. He has olive skin and dark, close-cropped hair, wearing traditional white chef\'s attire. Steam rises from the pan he\'s working with. The kitchen\'s stainless steel surfaces reflect the bright overhead lighting. The camera follows his hands as he cooks. The scene appears to be real-life footage.", "outWidth": 864, "outHeight": 480, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "negative_prompt": "low quality, worst quality, deformed, distorted, watermark", "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-10T00:19:43.347815Z", "created_at": "2025-01-10T00:10:33.433000Z", "data_removed": false, "error": null, "id": "gtnc7qk2b5rma0cm9p6ba4vsy0", "input": { "outFPS": 24, "myprompt": "A chef prepares food in a professional kitchen. He has olive skin and dark, close-cropped hair, wearing traditional white chef's attire. Steam rises from the pan he's working with. The kitchen's stainless steel surfaces reflect the bright overhead lighting. The camera follows his hands as he cooks. The scene appears to be real-life footage.", "outWidth": 864, "outHeight": 480, "num_frames": 97, "num_outputs": 1, "guidanceScale": 3, "negative_prompt": "low quality, worst quality, deformed, distorted, watermark", "num_inference_steps": 30 }, "logs": "Using seed: 36320\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:14, 2.01it/s]\n 7%|▋ | 2/30 [00:00<00:10, 2.68it/s]\n 10%|█ | 3/30 [00:01<00:11, 2.38it/s]\n 13%|█▎ | 4/30 [00:01<00:11, 2.26it/s]\n 17%|█▋ | 5/30 [00:02<00:11, 2.19it/s]\n 20%|██ | 6/30 [00:02<00:11, 2.16it/s]\n 23%|██▎ | 7/30 [00:03<00:10, 2.13it/s]\n 27%|██▋ | 8/30 [00:03<00:10, 2.12it/s]\n 30%|███ | 9/30 [00:04<00:09, 2.11it/s]\n 33%|███▎ | 10/30 [00:04<00:09, 2.10it/s]\n 37%|███▋ | 11/30 [00:05<00:09, 2.10it/s]\n 40%|████ | 12/30 [00:05<00:08, 2.09it/s]\n 43%|████▎ | 13/30 [00:06<00:08, 2.09it/s]\n 47%|████▋ | 14/30 [00:06<00:07, 2.09it/s]\n 50%|█████ | 15/30 [00:07<00:07, 2.09it/s]\n 53%|█████▎ | 16/30 [00:07<00:06, 2.09it/s]\n 57%|█████▋ | 17/30 [00:07<00:06, 2.08it/s]\n 60%|██████ | 18/30 [00:08<00:05, 2.08it/s]\n 63%|██████▎ | 19/30 [00:08<00:05, 2.08it/s]\n 67%|██████▋ | 20/30 [00:09<00:04, 2.08it/s]\n 70%|███████ | 21/30 [00:09<00:04, 2.08it/s]\n 73%|███████▎ | 22/30 [00:10<00:03, 2.08it/s]\n 77%|███████▋ | 23/30 [00:10<00:03, 2.08it/s]\n 80%|████████ | 24/30 [00:11<00:02, 2.08it/s]\n 83%|████████▎ | 25/30 [00:11<00:02, 2.08it/s]\n 87%|████████▋ | 26/30 [00:12<00:01, 2.08it/s]\n 90%|█████████ | 27/30 [00:12<00:01, 2.08it/s]\n 93%|█████████▎| 28/30 [00:13<00:00, 2.08it/s]\n 97%|█████████▋| 29/30 [00:13<00:00, 2.08it/s]\n100%|██████████| 30/30 [00:14<00:00, 2.08it/s]\n100%|██████████| 30/30 [00:14<00:00, 2.11it/s]", "metrics": { "predict_time": 16.597149806, "total_time": 549.914815 }, "output": "https://replicate.delivery/xezq/xUEUpDETrewoPSk04iCxBwytACHlcABIumKlojLC8A7PzwBKA/output.mp4", "started_at": "2025-01-10T00:19:26.750665Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-zmhg4c42ccaa3prbrpsbbhah4ktvxc6xksbgloqepvpityn73hoq", "get": "https://api.replicate.com/v1/predictions/gtnc7qk2b5rma0cm9p6ba4vsy0", "cancel": "https://api.replicate.com/v1/predictions/gtnc7qk2b5rma0cm9p6ba4vsy0/cancel" }, "version": "807fb8dfd1a0e77faed3e56dc11a0cfdd7433e4f35fb8ee7abe5abbafd27e189" }Generated inUsing seed: 36320 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:14, 2.01it/s] 7%|▋ | 2/30 [00:00<00:10, 2.68it/s] 10%|█ | 3/30 [00:01<00:11, 2.38it/s] 13%|█▎ | 4/30 [00:01<00:11, 2.26it/s] 17%|█▋ | 5/30 [00:02<00:11, 2.19it/s] 20%|██ | 6/30 [00:02<00:11, 2.16it/s] 23%|██▎ | 7/30 [00:03<00:10, 2.13it/s] 27%|██▋ | 8/30 [00:03<00:10, 2.12it/s] 30%|███ | 9/30 [00:04<00:09, 2.11it/s] 33%|███▎ | 10/30 [00:04<00:09, 2.10it/s] 37%|███▋ | 11/30 [00:05<00:09, 2.10it/s] 40%|████ | 12/30 [00:05<00:08, 2.09it/s] 43%|████▎ | 13/30 [00:06<00:08, 2.09it/s] 47%|████▋ | 14/30 [00:06<00:07, 2.09it/s] 50%|█████ | 15/30 [00:07<00:07, 2.09it/s] 53%|█████▎ | 16/30 [00:07<00:06, 2.09it/s] 57%|█████▋ | 17/30 [00:07<00:06, 2.08it/s] 60%|██████ | 18/30 [00:08<00:05, 2.08it/s] 63%|██████▎ | 19/30 [00:08<00:05, 2.08it/s] 67%|██████▋ | 20/30 [00:09<00:04, 2.08it/s] 70%|███████ | 21/30 [00:09<00:04, 2.08it/s] 73%|███████▎ | 22/30 [00:10<00:03, 2.08it/s] 77%|███████▋ | 23/30 [00:10<00:03, 2.08it/s] 80%|████████ | 24/30 [00:11<00:02, 2.08it/s] 83%|████████▎ | 25/30 [00:11<00:02, 2.08it/s] 87%|████████▋ | 26/30 [00:12<00:01, 2.08it/s] 90%|█████████ | 27/30 [00:12<00:01, 2.08it/s] 93%|█████████▎| 28/30 [00:13<00:00, 2.08it/s] 97%|█████████▋| 29/30 [00:13<00:00, 2.08it/s] 100%|██████████| 30/30 [00:14<00:00, 2.08it/s] 100%|██████████| 30/30 [00:14<00:00, 2.11it/s]Prediction
georgedavila/cog-ltx-video:fb52121156741fe3d012e22e723042d260fe27c2b1705e9f09ec7ac64d61827bID4tc2st3e51rma0cm9s8rv5gy7gStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- outFPS
- 24
- myprompt
- A realistic alien UFO from outer space flies over the a city shooting lasers at buildings. Buildings hit with red lasers start collapsing after a bright purple explosion. The shiny metal aircraft flies over the city on a bright sunny day, moving from the left side to the right side of out viewer. The camera stays stationary. The scene appears to be from a movie.
- outWidth
- 768
- outHeight
- 512
- num_frames
- 97
- num_outputs
- 4
- guidanceScale
- 3
- negative_prompt
- watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted
- decodeTimestepParam
- 0.03
- num_inference_steps
- 60
- decodeNoiseScaleParam
- 0.025
{ "outFPS": 24, "myprompt": "A realistic alien UFO from outer space flies over the a city shooting lasers at buildings. Buildings hit with red lasers start collapsing after a bright purple explosion. The shiny metal aircraft flies over the city on a bright sunny day, moving from the left side to the right side of out viewer. The camera stays stationary. The scene appears to be from a movie. ", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 4, "guidanceScale": 3, "negative_prompt": "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted", "decodeTimestepParam": 0.03, "num_inference_steps": 60, "decodeNoiseScaleParam": 0.025 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; 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:fb52121156741fe3d012e22e723042d260fe27c2b1705e9f09ec7ac64d61827b", { input: { outFPS: 24, myprompt: "A realistic alien UFO from outer space flies over the a city shooting lasers at buildings. Buildings hit with red lasers start collapsing after a bright purple explosion. The shiny metal aircraft flies over the city on a bright sunny day, moving from the left side to the right side of out viewer. The camera stays stationary. The scene appears to be from a movie. ", outWidth: 768, outHeight: 512, num_frames: 97, num_outputs: 4, guidanceScale: 3, negative_prompt: "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted", decodeTimestepParam: 0.03, num_inference_steps: 60, decodeNoiseScaleParam: 0.025 } } ); // 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.
Install Replicate’s Python client library:pip install replicateImport 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:fb52121156741fe3d012e22e723042d260fe27c2b1705e9f09ec7ac64d61827b", input={ "outFPS": 24, "myprompt": "A realistic alien UFO from outer space flies over the a city shooting lasers at buildings. Buildings hit with red lasers start collapsing after a bright purple explosion. The shiny metal aircraft flies over the city on a bright sunny day, moving from the left side to the right side of out viewer. The camera stays stationary. The scene appears to be from a movie. ", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 4, "guidanceScale": 3, "negative_prompt": "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted", "decodeTimestepParam": 0.03, "num_inference_steps": 60, "decodeNoiseScaleParam": 0.025 } ) print(output)To learn more, take a look at the guide on getting started with Python.
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:fb52121156741fe3d012e22e723042d260fe27c2b1705e9f09ec7ac64d61827b", "input": { "outFPS": 24, "myprompt": "A realistic alien UFO from outer space flies over the a city shooting lasers at buildings. Buildings hit with red lasers start collapsing after a bright purple explosion. The shiny metal aircraft flies over the city on a bright sunny day, moving from the left side to the right side of out viewer. The camera stays stationary. The scene appears to be from a movie. ", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 4, "guidanceScale": 3, "negative_prompt": "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted", "decodeTimestepParam": 0.03, "num_inference_steps": 60, "decodeNoiseScaleParam": 0.025 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-10T03:50:03.659242Z", "created_at": "2025-01-10T03:45:47.048000Z", "data_removed": false, "error": null, "id": "4tc2st3e51rma0cm9s8rv5gy7g", "input": { "outFPS": 24, "myprompt": "A realistic alien UFO from outer space flies over the a city shooting lasers at buildings. Buildings hit with red lasers start collapsing after a bright purple explosion. The shiny metal aircraft flies over the city on a bright sunny day, moving from the left side to the right side of out viewer. The camera stays stationary. The scene appears to be from a movie. ", "outWidth": 768, "outHeight": 512, "num_frames": 97, "num_outputs": 4, "guidanceScale": 3, "negative_prompt": "watermark, text, deformed, worst quality, inconsistent motion, blurry, jittery, distorted", "decodeTimestepParam": 0.03, "num_inference_steps": 60, "decodeNoiseScaleParam": 0.025 }, "logs": "Using seed: 33178\n 0%| | 0/60 [00:00<?, ?it/s]\n 2%|▏ | 1/60 [00:01<01:53, 1.93s/it]\n 3%|▎ | 2/60 [00:03<01:24, 1.46s/it]\n 5%|▌ | 3/60 [00:04<01:35, 1.67s/it]\n 7%|▋ | 4/60 [00:06<01:38, 1.77s/it]\n 8%|▊ | 5/60 [00:08<01:40, 1.82s/it]\n 10%|█ | 6/60 [00:10<01:40, 1.85s/it]\n 12%|█▏ | 7/60 [00:12<01:39, 1.87s/it]\n 13%|█▎ | 8/60 [00:14<01:38, 1.89s/it]\n 15%|█▌ | 9/60 [00:16<01:36, 1.90s/it]\n 17%|█▋ | 10/60 [00:18<01:35, 1.90s/it]\n 18%|█▊ | 11/60 [00:20<01:33, 1.91s/it]\n 20%|██ | 12/60 [00:22<01:31, 1.91s/it]\n 22%|██▏ | 13/60 [00:24<01:30, 1.92s/it]\n 23%|██▎ | 14/60 [00:26<01:28, 1.92s/it]\n 25%|██▌ | 15/60 [00:28<01:26, 1.92s/it]\n 27%|██▋ | 16/60 [00:29<01:24, 1.92s/it]\n 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[01:54<00:00, 1.92s/it]\n100%|██████████| 60/60 [01:54<00:00, 1.91s/it]", "metrics": { "predict_time": 124.218516845, "total_time": 256.611242 }, "output": [ "https://replicate.delivery/xezq/9J9m9OfXaryKHivArMIWH4Z3GzmB1h2kieSfJqsq02DXXJHoA/out-0.mp4", "https://replicate.delivery/xezq/iRNo7JcteYQ0VCGKaeDdXrMkWwxltuenmCrRhj7L88JWXJHoA/out-1.mp4", "https://replicate.delivery/xezq/tgeE0cIFsCTeEEtxUwXUoaR4dFsY6U5ug3pmNz9Q6aorrkDUA/out-2.mp4", "https://replicate.delivery/xezq/xy1aiCVAifwfm0GVmUxz87SAxGtP4W3OUDG7owQT9aQrrkDUA/out-3.mp4" ], "started_at": "2025-01-10T03:47:59.440725Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-ihwd3my4ktvj63bdm6owpjnvilg33p5dezjxlq3xdb37z6zds76q", "get": "https://api.replicate.com/v1/predictions/4tc2st3e51rma0cm9s8rv5gy7g", "cancel": "https://api.replicate.com/v1/predictions/4tc2st3e51rma0cm9s8rv5gy7g/cancel" }, "version": "fb52121156741fe3d012e22e723042d260fe27c2b1705e9f09ec7ac64d61827b" }Generated inUsing seed: 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