cjwbw
/
kandinskyvideo
text-to-video generation model
Prediction
cjwbw/kandinskyvideo:849b70f3IDjnvfjstbxqlangdvnwz3pqlh6uStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- fps
- 10
- width
- 640
- height
- 384
- prompt
- a red car is drifting on the mountain road, close view, fast movement
- guidance_scale
- 5
- interpolation_level
- low
- num_inference_steps
- 50
- interpolation_guidance_scale
- 0.25
{ "fps": 10, "width": 640, "height": 384, "prompt": "a red car is drifting on the mountain road, close view, fast movement", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }npm install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", { input: { fps: 10, width: 640, height: 384, prompt: "a red car is drifting on the mountain road, close view, fast movement", guidance_scale: 5, interpolation_level: "low", num_inference_steps: 50, interpolation_guidance_scale: 0.25 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the clientimport replicateRun cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", input={ "fps": 10, "width": 640, "height": 384, "prompt": "a red car is drifting on the mountain road, close view, fast movement", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run cjwbw/kandinskyvideo 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": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", "input": { "fps": 10, "width": 640, "height": 384, "prompt": "a red car is drifting on the mountain road, close view, fast movement", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run cjwbw/kandinskyvideo using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545 \ -i 'fps=10' \ -i 'width=640' \ -i 'height=384' \ -i 'prompt="a red car is drifting on the mountain road, close view, fast movement"' \ -i 'guidance_scale=5' \ -i 'interpolation_level="low"' \ -i 'num_inference_steps=50' \ -i 'interpolation_guidance_scale=0.25'To learn more, take a look at the Cog documentation.
Pull and run cjwbw/kandinskyvideo using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "fps": 10, "width": 640, "height": 384, "prompt": "a red car is drifting on the mountain road, close view, fast movement", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ http://localhost:5000/predictionsOutput
{ "completed_at": "2023-11-25T17:30:06.441672Z", "created_at": "2023-11-25T17:17:32.380766Z", "data_removed": false, "error": null, "id": "jnvfjstbxqlangdvnwz3pqlh6u", "input": { "fps": 10, "width": 640, "height": 384, "prompt": "a red car is drifting on the mountain road, close view, fast movement", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }, "logs": "0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:31, 1.57it/s]\n 4%|▍ | 2/50 [00:01<00:26, 1.81it/s]\n 6%|▌ | 3/50 [00:01<00:24, 1.91it/s]\n 8%|▊ | 4/50 [00:02<00:23, 1.96it/s]\n 10%|█ | 5/50 [00:02<00:22, 1.99it/s]\n 12%|█▏ | 6/50 [00:03<00:21, 2.01it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 2.02it/s]\n 16%|█▌ | 8/50 [00:04<00:20, 2.03it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 2.04it/s]\n 20%|██ | 10/50 [00:05<00:19, 2.04it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 2.03it/s]\n 24%|██▍ | 12/50 [00:06<00:18, 2.04it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 2.04it/s]\n 28%|██▊ | 14/50 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2.05it/s]\n 74%|███████▍ | 37/50 [00:18<00:06, 2.05it/s]\n 76%|███████▌ | 38/50 [00:18<00:05, 2.05it/s]\n 78%|███████▊ | 39/50 [00:19<00:05, 2.05it/s]\n 80%|████████ | 40/50 [00:19<00:04, 2.05it/s]\n 82%|████████▏ | 41/50 [00:20<00:04, 2.05it/s]\n 84%|████████▍ | 42/50 [00:20<00:03, 2.05it/s]\n 86%|████████▌ | 43/50 [00:21<00:03, 2.05it/s]\n 88%|████████▊ | 44/50 [00:21<00:02, 2.05it/s]\n 90%|█████████ | 45/50 [00:22<00:02, 2.05it/s]\n 92%|█████████▏| 46/50 [00:22<00:01, 2.05it/s]\n 94%|█████████▍| 47/50 [00:23<00:01, 2.05it/s]\n 96%|█████████▌| 48/50 [00:23<00:00, 2.05it/s]\n 98%|█████████▊| 49/50 [00:24<00:00, 2.05it/s]\n100%|██████████| 50/50 [00:24<00:00, 2.05it/s]\n100%|██████████| 50/50 [00:24<00:00, 2.03it/s]", "metrics": { "predict_time": 28.07745, "total_time": 754.060906 }, "output": "https://replicate.delivery/pbxt/ESLBl1hGLVZiJ5NEMoksjLY0Rf9CG3Xwb5jZBGrn8hoOCf7RA/output.mp4", "started_at": "2023-11-25T17:29:38.364222Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jnvfjstbxqlangdvnwz3pqlh6u", "cancel": "https://api.replicate.com/v1/predictions/jnvfjstbxqlangdvnwz3pqlh6u/cancel" }, "version": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545" }Generated in0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:31, 1.57it/s] 4%|▍ | 2/50 [00:01<00:26, 1.81it/s] 6%|▌ | 3/50 [00:01<00:24, 1.91it/s] 8%|▊ | 4/50 [00:02<00:23, 1.96it/s] 10%|█ | 5/50 [00:02<00:22, 1.99it/s] 12%|█▏ | 6/50 [00:03<00:21, 2.01it/s] 14%|█▍ | 7/50 [00:03<00:21, 2.02it/s] 16%|█▌ | 8/50 [00:04<00:20, 2.03it/s] 18%|█▊ | 9/50 [00:04<00:20, 2.04it/s] 20%|██ | 10/50 [00:05<00:19, 2.04it/s] 22%|██▏ | 11/50 [00:05<00:19, 2.03it/s] 24%|██▍ | 12/50 [00:06<00:18, 2.04it/s] 26%|██▌ | 13/50 [00:06<00:18, 2.04it/s] 28%|██▊ | 14/50 [00:06<00:17, 2.04it/s] 30%|███ | 15/50 [00:07<00:17, 2.05it/s] 32%|███▏ | 16/50 [00:07<00:16, 2.05it/s] 34%|███▍ | 17/50 [00:08<00:16, 2.05it/s] 36%|███▌ | 18/50 [00:08<00:15, 2.05it/s] 38%|███▊ | 19/50 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cjwbw/kandinskyvideo:849b70f3IDyo6uje3bvgx5gsv65lc4kouf54StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- fps
- 10
- width
- 640
- height
- 384
- prompt
- A car moving on the road from the sea to the mountains
- guidance_scale
- 5
- interpolation_level
- medium
- num_inference_steps
- 50
- interpolation_guidance_scale
- 0.25
{ "fps": 10, "width": 640, "height": 384, "prompt": "A car moving on the road from the sea to the mountains", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }npm install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", { input: { fps: 10, width: 640, height: 384, prompt: "A car moving on the road from the sea to the mountains", guidance_scale: 5, interpolation_level: "medium", num_inference_steps: 50, interpolation_guidance_scale: 0.25 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the clientimport replicateRun cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", input={ "fps": 10, "width": 640, "height": 384, "prompt": "A car moving on the road from the sea to the mountains", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run cjwbw/kandinskyvideo 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": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", "input": { "fps": 10, "width": 640, "height": 384, "prompt": "A car moving on the road from the sea to the mountains", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run cjwbw/kandinskyvideo using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545 \ -i 'fps=10' \ -i 'width=640' \ -i 'height=384' \ -i 'prompt="A car moving on the road from the sea to the mountains"' \ -i 'guidance_scale=5' \ -i 'interpolation_level="medium"' \ -i 'num_inference_steps=50' \ -i 'interpolation_guidance_scale=0.25'To learn more, take a look at the Cog documentation.
Pull and run cjwbw/kandinskyvideo using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "fps": 10, "width": 640, "height": 384, "prompt": "A car moving on the road from the sea to the mountains", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ http://localhost:5000/predictionsOutput
{ "completed_at": "2023-11-25T17:44:54.292039Z", "created_at": "2023-11-25T17:44:01.529258Z", "data_removed": false, "error": null, "id": "yo6uje3bvgx5gsv65lc4kouf54", "input": { "fps": 10, "width": 640, "height": 384, "prompt": "A car moving on the road from the sea to the mountains", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }, "logs": "0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:23, 2.06it/s]\n 4%|▍ | 2/50 [00:00<00:23, 2.06it/s]\n 6%|▌ | 3/50 [00:01<00:22, 2.06it/s]\n 8%|▊ | 4/50 [00:01<00:22, 2.06it/s]\n 10%|█ | 5/50 [00:02<00:21, 2.06it/s]\n 12%|█▏ | 6/50 [00:02<00:21, 2.06it/s]\n 14%|█▍ | 7/50 [00:03<00:20, 2.06it/s]\n 16%|█▌ | 8/50 [00:03<00:20, 2.06it/s]\n 18%|█▊ | 9/50 [00:04<00:19, 2.06it/s]\n 20%|██ | 10/50 [00:04<00:19, 2.05it/s]\n 22%|██▏ | 11/50 [00:05<00:18, 2.06it/s]\n 24%|██▍ | 12/50 [00:05<00:18, 2.06it/s]\n 26%|██▌ | 13/50 [00:06<00:17, 2.06it/s]\n 28%|██▊ | 14/50 [00:06<00:17, 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[00:21<00:00, 2.35it/s]", "metrics": { "predict_time": 52.719358, "total_time": 52.762781 }, "output": "https://replicate.delivery/pbxt/nYj28RyKeJy2eUf04R1rFsDF6ntyOtdGumKhXRr1FiMrk83jA/output.mp4", "started_at": "2023-11-25T17:44:01.572681Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/yo6uje3bvgx5gsv65lc4kouf54", "cancel": "https://api.replicate.com/v1/predictions/yo6uje3bvgx5gsv65lc4kouf54/cancel" }, "version": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545" }Generated in0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:23, 2.06it/s] 4%|▍ | 2/50 [00:00<00:23, 2.06it/s] 6%|▌ | 3/50 [00:01<00:22, 2.06it/s] 8%|▊ | 4/50 [00:01<00:22, 2.06it/s] 10%|█ | 5/50 [00:02<00:21, 2.06it/s] 12%|█▏ | 6/50 [00:02<00:21, 2.06it/s] 14%|█▍ | 7/50 [00:03<00:20, 2.06it/s] 16%|█▌ | 8/50 [00:03<00:20, 2.06it/s] 18%|█▊ | 9/50 [00:04<00:19, 2.06it/s] 20%|██ | 10/50 [00:04<00:19, 2.05it/s] 22%|██▏ | 11/50 [00:05<00:18, 2.06it/s] 24%|██▍ | 12/50 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cjwbw/kandinskyvideo:849b70f3IDzdatwflbzwigqfkthx35v23nyaStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- fps
- 10
- width
- 640
- height
- 384
- prompt
- Luminescent jellyfish swims underwater, neon, 4k
- guidance_scale
- 5
- interpolation_level
- low
- num_inference_steps
- 50
- interpolation_guidance_scale
- 0.25
{ "fps": 10, "width": 640, "height": 384, "prompt": "Luminescent jellyfish swims underwater, neon, 4k", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }npm install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", { input: { fps: 10, width: 640, height: 384, prompt: "Luminescent jellyfish swims underwater, neon, 4k", guidance_scale: 5, interpolation_level: "low", num_inference_steps: 50, interpolation_guidance_scale: 0.25 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the clientimport replicateRun cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", input={ "fps": 10, "width": 640, "height": 384, "prompt": "Luminescent jellyfish swims underwater, neon, 4k", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run cjwbw/kandinskyvideo 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": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", "input": { "fps": 10, "width": 640, "height": 384, "prompt": "Luminescent jellyfish swims underwater, neon, 4k", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run cjwbw/kandinskyvideo using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545 \ -i 'fps=10' \ -i 'width=640' \ -i 'height=384' \ -i 'prompt="Luminescent jellyfish swims underwater, neon, 4k"' \ -i 'guidance_scale=5' \ -i 'interpolation_level="low"' \ -i 'num_inference_steps=50' \ -i 'interpolation_guidance_scale=0.25'To learn more, take a look at the Cog documentation.
Pull and run cjwbw/kandinskyvideo using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "fps": 10, "width": 640, "height": 384, "prompt": "Luminescent jellyfish swims underwater, neon, 4k", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ http://localhost:5000/predictionsOutput
{ "completed_at": "2023-11-25T17:52:51.514798Z", "created_at": "2023-11-25T17:52:24.129163Z", "data_removed": false, "error": null, "id": "zdatwflbzwigqfkthx35v23nya", "input": { "fps": 10, "width": 640, "height": 384, "prompt": "Luminescent jellyfish swims underwater, neon, 4k", "guidance_scale": 5, "interpolation_level": "low", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }, "logs": "0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:24, 2.04it/s]\n 4%|▍ | 2/50 [00:00<00:23, 2.05it/s]\n 6%|▌ | 3/50 [00:01<00:22, 2.05it/s]\n 8%|▊ | 4/50 [00:01<00:22, 2.05it/s]\n 10%|█ | 5/50 [00:02<00:21, 2.05it/s]\n 12%|█▏ | 6/50 [00:02<00:21, 2.05it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 2.05it/s]\n 16%|█▌ | 8/50 [00:03<00:20, 2.05it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 2.05it/s]\n 20%|██ | 10/50 [00:04<00:19, 2.05it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 2.05it/s]\n 24%|██▍ | 12/50 [00:05<00:18, 2.05it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 2.05it/s]\n 28%|██▊ | 14/50 [00:06<00:17, 2.05it/s]\n 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[00:18<00:06, 2.05it/s]\n 76%|███████▌ | 38/50 [00:18<00:05, 2.05it/s]\n 78%|███████▊ | 39/50 [00:19<00:05, 2.05it/s]\n 80%|████████ | 40/50 [00:19<00:04, 2.05it/s]\n 82%|████████▏ | 41/50 [00:20<00:04, 2.05it/s]\n 84%|████████▍ | 42/50 [00:20<00:03, 2.05it/s]\n 86%|████████▌ | 43/50 [00:20<00:03, 2.05it/s]\n 88%|████████▊ | 44/50 [00:21<00:02, 2.05it/s]\n 90%|█████████ | 45/50 [00:21<00:02, 2.05it/s]\n 92%|█████████▏| 46/50 [00:22<00:01, 2.05it/s]\n 94%|█████████▍| 47/50 [00:22<00:01, 2.05it/s]\n 96%|█████████▌| 48/50 [00:23<00:00, 2.04it/s]\n 98%|█████████▊| 49/50 [00:23<00:00, 2.05it/s]\n100%|██████████| 50/50 [00:24<00:00, 2.05it/s]\n100%|██████████| 50/50 [00:24<00:00, 2.05it/s]", "metrics": { "predict_time": 27.348982, "total_time": 27.385635 }, "output": "https://replicate.delivery/pbxt/Ull3DAmK7eQsDiNKOtRE6FJqDMhkrMAYeMfTv1eqUKtIn5vHB/output.mp4", "started_at": "2023-11-25T17:52:24.165816Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zdatwflbzwigqfkthx35v23nya", "cancel": "https://api.replicate.com/v1/predictions/zdatwflbzwigqfkthx35v23nya/cancel" }, "version": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545" }Generated in0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:24, 2.04it/s] 4%|▍ | 2/50 [00:00<00:23, 2.05it/s] 6%|▌ | 3/50 [00:01<00:22, 2.05it/s] 8%|▊ | 4/50 [00:01<00:22, 2.05it/s] 10%|█ | 5/50 [00:02<00:21, 2.05it/s] 12%|█▏ | 6/50 [00:02<00:21, 2.05it/s] 14%|█▍ | 7/50 [00:03<00:21, 2.05it/s] 16%|█▌ | 8/50 [00:03<00:20, 2.05it/s] 18%|█▊ | 9/50 [00:04<00:20, 2.05it/s] 20%|██ | 10/50 [00:04<00:19, 2.05it/s] 22%|██▏ | 11/50 [00:05<00:19, 2.05it/s] 24%|██▍ | 12/50 [00:05<00:18, 2.05it/s] 26%|██▌ | 13/50 [00:06<00:18, 2.05it/s] 28%|██▊ | 14/50 [00:06<00:17, 2.05it/s] 30%|███ | 15/50 [00:07<00:17, 2.05it/s] 32%|███▏ | 16/50 [00:07<00:16, 2.05it/s] 34%|███▍ | 17/50 [00:08<00:16, 2.05it/s] 36%|███▌ | 18/50 [00:08<00:15, 2.05it/s] 38%|███▊ | 19/50 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cjwbw/kandinskyvideo:849b70f3IDur4spwdbmlpbjvhqp6za3vrurmStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- fps
- 10
- width
- 512
- height
- 512
- prompt
- Explore the fascinating world of underwater creatures in a visually stunning sequence
- guidance_scale
- 5
- interpolation_level
- medium
- num_inference_steps
- 50
- interpolation_guidance_scale
- 0.25
{ "fps": 10, "width": 512, "height": 512, "prompt": "Explore the fascinating world of underwater creatures in a visually stunning sequence", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }npm install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", { input: { fps: 10, width: 512, height: 512, prompt: "Explore the fascinating world of underwater creatures in a visually stunning sequence", guidance_scale: 5, interpolation_level: "medium", num_inference_steps: 50, interpolation_guidance_scale: 0.25 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the clientimport replicateRun cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", input={ "fps": 10, "width": 512, "height": 512, "prompt": "Explore the fascinating world of underwater creatures in a visually stunning sequence", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run cjwbw/kandinskyvideo 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": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", "input": { "fps": 10, "width": 512, "height": 512, "prompt": "Explore the fascinating world of underwater creatures in a visually stunning sequence", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run cjwbw/kandinskyvideo using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545 \ -i 'fps=10' \ -i 'width=512' \ -i 'height=512' \ -i 'prompt="Explore the fascinating world of underwater creatures in a visually stunning sequence"' \ -i 'guidance_scale=5' \ -i 'interpolation_level="medium"' \ -i 'num_inference_steps=50' \ -i 'interpolation_guidance_scale=0.25'To learn more, take a look at the Cog documentation.
Pull and run cjwbw/kandinskyvideo using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "fps": 10, "width": 512, "height": 512, "prompt": "Explore the fascinating world of underwater creatures in a visually stunning sequence", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ http://localhost:5000/predictionsOutput
{ "completed_at": "2023-11-25T17:56:49.440758Z", "created_at": "2023-11-25T17:55:54.189327Z", "data_removed": false, "error": null, "id": "ur4spwdbmlpbjvhqp6za3vrurm", "input": { "fps": 10, "width": 512, "height": 512, "prompt": "Explore the fascinating world of underwater creatures in a visually stunning sequence", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }, "logs": "0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:25, 1.95it/s]\n 4%|▍ | 2/50 [00:01<00:24, 1.97it/s]\n 6%|▌ | 3/50 [00:01<00:23, 1.98it/s]\n 8%|▊ | 4/50 [00:02<00:23, 1.98it/s]\n 10%|█ | 5/50 [00:02<00:22, 1.99it/s]\n 12%|█▏ | 6/50 [00:03<00:22, 1.98it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 1.98it/s]\n 16%|█▌ | 8/50 [00:04<00:21, 1.99it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 1.99it/s]\n 20%|██ | 10/50 [00:05<00:20, 1.99it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 1.99it/s]\n 24%|██▍ | 12/50 [00:06<00:19, 1.99it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 1.98it/s]\n 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2.24it/s]\n100%|██████████| 50/50 [00:22<00:00, 2.24it/s]", "metrics": { "predict_time": 55.214352, "total_time": 55.251431 }, "output": "https://replicate.delivery/pbxt/edADJTJxzAxbG6PImZ78MZ7yBPtg4ttIrOQcwTRqxBawOf7RA/output.mp4", "started_at": "2023-11-25T17:55:54.226406Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ur4spwdbmlpbjvhqp6za3vrurm", "cancel": "https://api.replicate.com/v1/predictions/ur4spwdbmlpbjvhqp6za3vrurm/cancel" }, "version": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545" }Generated in0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:25, 1.95it/s] 4%|▍ | 2/50 [00:01<00:24, 1.97it/s] 6%|▌ | 3/50 [00:01<00:23, 1.98it/s] 8%|▊ | 4/50 [00:02<00:23, 1.98it/s] 10%|█ | 5/50 [00:02<00:22, 1.99it/s] 12%|█▏ | 6/50 [00:03<00:22, 1.98it/s] 14%|█▍ | 7/50 [00:03<00:21, 1.98it/s] 16%|█▌ | 8/50 [00:04<00:21, 1.99it/s] 18%|█▊ | 9/50 [00:04<00:20, 1.99it/s] 20%|██ | 10/50 [00:05<00:20, 1.99it/s] 22%|██▏ | 11/50 [00:05<00:19, 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cjwbw/kandinskyvideo:849b70f3ID7xxbg6lbez7hjhzhbnno6fpe44StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- fps
- 10
- width
- 640
- height
- 384
- prompt
- Rolling waves on a sandy beach relaxation, rhythm, and coastal beauty
- guidance_scale
- 5
- interpolation_level
- medium
- num_inference_steps
- 50
- interpolation_guidance_scale
- 0.25
{ "fps": 10, "width": 640, "height": 384, "prompt": "Rolling waves on a sandy beach relaxation, rhythm, and coastal beauty", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }npm install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", { input: { fps: 10, width: 640, height: 384, prompt: "Rolling waves on a sandy beach relaxation, rhythm, and coastal beauty", guidance_scale: 5, interpolation_level: "medium", num_inference_steps: 50, interpolation_guidance_scale: 0.25 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the clientimport replicateRun cjwbw/kandinskyvideo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/kandinskyvideo:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", input={ "fps": 10, "width": 640, "height": 384, "prompt": "Rolling waves on a sandy beach relaxation, rhythm, and coastal beauty", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run cjwbw/kandinskyvideo 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": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545", "input": { "fps": 10, "width": 640, "height": 384, "prompt": "Rolling waves on a sandy beach relaxation, rhythm, and coastal beauty", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run cjwbw/kandinskyvideo using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545 \ -i 'fps=10' \ -i 'width=640' \ -i 'height=384' \ -i 'prompt="Rolling waves on a sandy beach relaxation, rhythm, and coastal beauty"' \ -i 'guidance_scale=5' \ -i 'interpolation_level="medium"' \ -i 'num_inference_steps=50' \ -i 'interpolation_guidance_scale=0.25'To learn more, take a look at the Cog documentation.
Pull and run cjwbw/kandinskyvideo using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/cjwbw/kandinskyvideo@sha256:849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "fps": 10, "width": 640, "height": 384, "prompt": "Rolling waves on a sandy beach relaxation, rhythm, and coastal beauty", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 } }' \ http://localhost:5000/predictionsOutput
{ "completed_at": "2023-11-25T17:57:42.620384Z", "created_at": "2023-11-25T17:56:27.402240Z", "data_removed": false, "error": null, "id": "7xxbg6lbez7hjhzhbnno6fpe44", "input": { "fps": 10, "width": 640, "height": 384, "prompt": "Rolling waves on a sandy beach relaxation, rhythm, and coastal beauty", "guidance_scale": 5, "interpolation_level": "medium", "num_inference_steps": 50, "interpolation_guidance_scale": 0.25 }, "logs": "0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:23, 2.05it/s]\n 4%|▍ | 2/50 [00:00<00:23, 2.05it/s]\n 6%|▌ | 3/50 [00:01<00:23, 2.04it/s]\n 8%|▊ | 4/50 [00:01<00:22, 2.04it/s]\n 10%|█ | 5/50 [00:02<00:21, 2.05it/s]\n 12%|█▏ | 6/50 [00:02<00:21, 2.04it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 2.04it/s]\n 16%|█▌ | 8/50 [00:03<00:20, 2.05it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 2.05it/s]\n 20%|██ | 10/50 [00:04<00:19, 2.05it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 2.05it/s]\n 24%|██▍ | 12/50 [00:05<00:18, 2.04it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 2.05it/s]\n 28%|██▊ | 14/50 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[00:21<00:00, 2.35it/s]", "metrics": { "predict_time": 52.905414, "total_time": 75.218144 }, "output": "https://replicate.delivery/pbxt/WC6egtZeV7uHeJsefOUPjvNXqmHNWUiyGidGVfBeVN8yKPf7RA/output.mp4", "started_at": "2023-11-25T17:56:49.714970Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7xxbg6lbez7hjhzhbnno6fpe44", "cancel": "https://api.replicate.com/v1/predictions/7xxbg6lbez7hjhzhbnno6fpe44/cancel" }, "version": "849b70f3e300a650aa8b78d0f8f24d104824b832ea7f61c79bd2c7e78a4ad545" }Generated in0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:23, 2.05it/s] 4%|▍ | 2/50 [00:00<00:23, 2.05it/s] 6%|▌ | 3/50 [00:01<00:23, 2.04it/s] 8%|▊ | 4/50 [00:01<00:22, 2.04it/s] 10%|█ | 5/50 [00:02<00:21, 2.05it/s] 12%|█▏ | 6/50 [00:02<00:21, 2.04it/s] 14%|█▍ | 7/50 [00:03<00:21, 2.04it/s] 16%|█▌ | 8/50 [00:03<00:20, 2.05it/s] 18%|█▊ | 9/50 [00:04<00:20, 2.05it/s] 20%|██ | 10/50 [00:04<00:19, 2.05it/s] 22%|██▏ | 11/50 [00:05<00:19, 2.05it/s] 24%|██▍ | 12/50 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