mtg / music-approachability-engagement
Classification of music approachability and engagement
Prediction
mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cdaIDvtsqoqr2j5ayfcye6fhyoucaoaStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%00:00:000Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
{ "audio": "https://replicate.delivery/mgxm/9a5ea44f-239d-4469-be05-2416d648f28c/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", { input: { audio: "https://replicate.delivery/mgxm/9a5ea44f-239d-4469-be05-2416d648f28c/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", input={ "audio": "https://replicate.delivery/mgxm/9a5ea44f-239d-4469-be05-2416d648f28c/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", "input": { "audio": "https://replicate.delivery/mgxm/9a5ea44f-239d-4469-be05-2416d648f28c/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
Rendering markdown...
{ "completed_at": "2022-04-08T18:15:53.881225Z", "created_at": "2022-04-08T18:15:40.967369Z", "data_removed": false, "error": null, "id": "vtsqoqr2j5ayfcye6fhyoucaoa", "input": { "audio": "https://replicate.delivery/mgxm/9a5ea44f-239d-4469-be05-2416d648f28c/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav" }, "logs": null, "metrics": { "predict_time": 12.722445, "total_time": 12.913856 }, "output": "https://replicate.delivery/mgxm/2ee49ea1-8817-4ffc-bdd4-f570012956ea/out.md", "started_at": "2022-04-08T18:15:41.158780Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vtsqoqr2j5ayfcye6fhyoucaoa", "cancel": "https://api.replicate.com/v1/predictions/vtsqoqr2j5ayfcye6fhyoucaoa/cancel" }, "version": "b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda" }Generated inPrediction
mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cdaIDtftglwjx35fphenz6e6mo3magyStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
No compatible source was found for this media.Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
{ "audio": "https://replicate.delivery/mgxm/a2da2519-d98c-4e67-9a40-f7d544d43e2f/02_-_Bad_Bunny_-_La_Dificil.flac" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", { input: { audio: "https://replicate.delivery/mgxm/a2da2519-d98c-4e67-9a40-f7d544d43e2f/02_-_Bad_Bunny_-_La_Dificil.flac" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", input={ "audio": "https://replicate.delivery/mgxm/a2da2519-d98c-4e67-9a40-f7d544d43e2f/02_-_Bad_Bunny_-_La_Dificil.flac" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", "input": { "audio": "https://replicate.delivery/mgxm/a2da2519-d98c-4e67-9a40-f7d544d43e2f/02_-_Bad_Bunny_-_La_Dificil.flac" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2022-04-08T18:40:20.384080Z", "created_at": "2022-04-08T18:40:09.927670Z", "data_removed": false, "error": null, "id": "tftglwjx35fphenz6e6mo3magy", "input": { "audio": "https://replicate.delivery/mgxm/a2da2519-d98c-4e67-9a40-f7d544d43e2f/02_-_Bad_Bunny_-_La_Dificil.flac" }, "logs": null, "metrics": { "predict_time": 10.273334, "total_time": 10.45641 }, "output": "https://replicate.delivery/mgxm/8f9acdd0-9ca6-455a-b8c9-d672c640bfe1/out.md", "started_at": "2022-04-08T18:40:10.110746Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tftglwjx35fphenz6e6mo3magy", "cancel": "https://api.replicate.com/v1/predictions/tftglwjx35fphenz6e6mo3magy/cancel" }, "version": "b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda" }Generated inPrediction
mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cdaID3uyiodvnvvhqdbchrqtlu4nbpiStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%00:00:000Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
{ "audio": "https://replicate.delivery/mgxm/b94224a4-27c1-4d73-9c44-6c649369d68a/01-bohemian_rhapsody.mp3" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", { input: { audio: "https://replicate.delivery/mgxm/b94224a4-27c1-4d73-9c44-6c649369d68a/01-bohemian_rhapsody.mp3" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", input={ "audio": "https://replicate.delivery/mgxm/b94224a4-27c1-4d73-9c44-6c649369d68a/01-bohemian_rhapsody.mp3" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", "input": { "audio": "https://replicate.delivery/mgxm/b94224a4-27c1-4d73-9c44-6c649369d68a/01-bohemian_rhapsody.mp3" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2022-04-08T18:16:32.965338Z", "created_at": "2022-04-08T18:16:28.308448Z", "data_removed": false, "error": null, "id": "3uyiodvnvvhqdbchrqtlu4nbpi", "input": { "audio": "https://replicate.delivery/mgxm/b94224a4-27c1-4d73-9c44-6c649369d68a/01-bohemian_rhapsody.mp3" }, "logs": null, "metrics": { "predict_time": 4.480675, "total_time": 4.65689 }, "output": "https://replicate.delivery/mgxm/de415a0f-9755-44f8-8e80-e4cbb75981aa/out.md", "started_at": "2022-04-08T18:16:28.484663Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3uyiodvnvvhqdbchrqtlu4nbpi", "cancel": "https://api.replicate.com/v1/predictions/3uyiodvnvvhqdbchrqtlu4nbpi/cancel" }, "version": "b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda" }Generated inPrediction
mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cdaID5vvnhfqsazfxziuhxtv2prj4yaStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
No compatible source was found for this media.Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
{ "audio": "https://replicate.delivery/mgxm/2134428c-6f4e-4867-9cc1-e134e6dad458/Villalar_-_VILLALAR_I_-_04_Pelabravo.flac" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", { input: { audio: "https://replicate.delivery/mgxm/2134428c-6f4e-4867-9cc1-e134e6dad458/Villalar_-_VILLALAR_I_-_04_Pelabravo.flac" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", input={ "audio": "https://replicate.delivery/mgxm/2134428c-6f4e-4867-9cc1-e134e6dad458/Villalar_-_VILLALAR_I_-_04_Pelabravo.flac" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", "input": { "audio": "https://replicate.delivery/mgxm/2134428c-6f4e-4867-9cc1-e134e6dad458/Villalar_-_VILLALAR_I_-_04_Pelabravo.flac" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2022-04-08T18:42:45.495885Z", "created_at": "2022-04-08T18:42:26.497584Z", "data_removed": false, "error": null, "id": "5vvnhfqsazfxziuhxtv2prj4ya", "input": { "audio": "https://replicate.delivery/mgxm/2134428c-6f4e-4867-9cc1-e134e6dad458/Villalar_-_VILLALAR_I_-_04_Pelabravo.flac" }, "logs": null, "metrics": { "predict_time": 18.616804, "total_time": 18.998301 }, "output": "https://replicate.delivery/mgxm/bb02bfd9-9da3-44b8-8688-b11262206114/out.md", "started_at": "2022-04-08T18:42:26.879081Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5vvnhfqsazfxziuhxtv2prj4ya", "cancel": "https://api.replicate.com/v1/predictions/5vvnhfqsazfxziuhxtv2prj4ya/cancel" }, "version": "b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda" }Generated inPrediction
mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cdaIDuvi7vuiiybgkto7p556ummjxaaStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%00:00:000Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
{ "audio": "https://replicate.delivery/mgxm/afc9b19a-6b75-4a6d-ba3f-6d523fc3af65/03_Marigold.mp3" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", { input: { audio: "https://replicate.delivery/mgxm/afc9b19a-6b75-4a6d-ba3f-6d523fc3af65/03_Marigold.mp3" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", input={ "audio": "https://replicate.delivery/mgxm/afc9b19a-6b75-4a6d-ba3f-6d523fc3af65/03_Marigold.mp3" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda", "input": { "audio": "https://replicate.delivery/mgxm/afc9b19a-6b75-4a6d-ba3f-6d523fc3af65/03_Marigold.mp3" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2022-04-08T18:39:16.180648Z", "created_at": "2022-04-08T18:38:58.427804Z", "data_removed": false, "error": null, "id": "uvi7vuiiybgkto7p556ummjxaa", "input": { "audio": "https://replicate.delivery/mgxm/afc9b19a-6b75-4a6d-ba3f-6d523fc3af65/03_Marigold.mp3" }, "logs": null, "metrics": { "predict_time": 17.586574, "total_time": 17.752844 }, "output": "https://replicate.delivery/mgxm/135de6d6-c4a4-4d11-8748-c54b39cdc5ca/out.md", "started_at": "2022-04-08T18:38:58.594074Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/uvi7vuiiybgkto7p556ummjxaa", "cancel": "https://api.replicate.com/v1/predictions/uvi7vuiiybgkto7p556ummjxaa/cancel" }, "version": "b4894e446003bd1313801b39bf62a48273fad49edff8fde97071984bcc312cda" }Generated inPrediction
mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96IDxuwomftygrhdppkrydkex7uxemStatusSucceededSourceWebHardwareCPUTotal durationCreatedInput
- url
- https://www.youtube.com/watch?v=7zp1TbLFPp8
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%00:00:000Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- model_type
- effnet-discogs-test-3class
{ "url": "https://www.youtube.com/watch?v=7zp1TbLFPp8", "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", "model_type": "effnet-discogs-test-3class" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96", { input: { url: "https://www.youtube.com/watch?v=7zp1TbLFPp8", audio: "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", model_type: "effnet-discogs-test-3class" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96", input={ "url": "https://www.youtube.com/watch?v=7zp1TbLFPp8", "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", "model_type": "effnet-discogs-test-3class" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96", "input": { "url": "https://www.youtube.com/watch?v=7zp1TbLFPp8", "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", "model_type": "effnet-discogs-test-3class" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2023-05-25T09:53:38.577233Z", "created_at": "2023-05-25T09:53:26.782312Z", "data_removed": false, "error": null, "id": "xuwomftygrhdppkrydkex7uxem", "input": { "url": "https://www.youtube.com/watch?v=7zp1TbLFPp8", "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", "model_type": "effnet-discogs-test-3class" }, "logs": "Warning: Both `url` and `audio` inputs were specified. The `url` will be process. To process the `audio` input clear the `url` input field.\n[youtube] 7zp1TbLFPp8: Downloading webpage\n[youtube] 7zp1TbLFPp8: Downloading player 41b8bed0\n[dashsegments] Total fragments: 1\n[download] Destination: /tmp/tmpcrpzmo5l/audio.webm\n[download] 0.0% of ~3.69MiB at 12.07KiB/s ETA 05:13\n[download] 0.1% of ~3.69MiB at 36.14KiB/s ETA 01:44\n[download] 0.2% of ~3.69MiB at 84.15KiB/s ETA 00:44\n[download] 0.4% of ~3.69MiB at 179.39KiB/s ETA 00:20\n[download] 0.8% of ~3.69MiB at 365.14KiB/s ETA 00:10\n[download] 1.7% of ~3.69MiB at 628.36KiB/s ETA 00:05\n[download] 3.4% of ~3.69MiB at 1.10MiB/s ETA 00:03\n[download] 6.7% of ~3.69MiB at 1.88MiB/s ETA 00:01\n[download] 13.5% of ~3.69MiB at 3.60MiB/s ETA 00:00\n[download] 27.0% of ~3.69MiB at 5.76MiB/s ETA 00:00\n[download] 54.1% of ~3.69MiB at 9.47MiB/s ETA 00:00\n[download] 100.0% of ~3.69MiB at 16.50MiB/s ETA 00:00\n[download] 100.0% of ~3.69MiB at 16.45MiB/s ETA 00:00\n[download] 100% of 3.69MiB in 00:00\n[ffmpeg] Destination: /tmp/tmpcrpzmo5l/audio.wav\nDeleting original file /tmp/tmpcrpzmo5l/audio.webm (pass -k to keep)\nloading audio...\nrunning classification heads...\n2023-05-25 09:53:35.885714: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\n[ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-3class.pb`\n[ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-3class.pb`\ndone!", "metrics": { "predict_time": 11.739723, "total_time": 11.794921 }, "output": "https://replicate.delivery/pbxt/9QHmo1buBp5TOhJVliul8HWMnaZgacRChRVyeD3IK5JREnfQA/out.md", "started_at": "2023-05-25T09:53:26.837510Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xuwomftygrhdppkrydkex7uxem", "cancel": "https://api.replicate.com/v1/predictions/xuwomftygrhdppkrydkex7uxem/cancel" }, "version": "386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96" }Generated inWarning: Both `url` and `audio` inputs were specified. The `url` will be process. To process the `audio` input clear the `url` input field. [youtube] 7zp1TbLFPp8: Downloading webpage [youtube] 7zp1TbLFPp8: Downloading player 41b8bed0 [dashsegments] Total fragments: 1 [download] Destination: /tmp/tmpcrpzmo5l/audio.webm [download] 0.0% of ~3.69MiB at 12.07KiB/s ETA 05:13 [download] 0.1% of ~3.69MiB at 36.14KiB/s ETA 01:44 [download] 0.2% of ~3.69MiB at 84.15KiB/s ETA 00:44 [download] 0.4% of ~3.69MiB at 179.39KiB/s ETA 00:20 [download] 0.8% of ~3.69MiB at 365.14KiB/s ETA 00:10 [download] 1.7% of ~3.69MiB at 628.36KiB/s ETA 00:05 [download] 3.4% of ~3.69MiB at 1.10MiB/s ETA 00:03 [download] 6.7% of ~3.69MiB at 1.88MiB/s ETA 00:01 [download] 13.5% of ~3.69MiB at 3.60MiB/s ETA 00:00 [download] 27.0% of ~3.69MiB at 5.76MiB/s ETA 00:00 [download] 54.1% of ~3.69MiB at 9.47MiB/s ETA 00:00 [download] 100.0% of ~3.69MiB at 16.50MiB/s ETA 00:00 [download] 100.0% of ~3.69MiB at 16.45MiB/s ETA 00:00 [download] 100% of 3.69MiB in 00:00 [ffmpeg] Destination: /tmp/tmpcrpzmo5l/audio.wav Deleting original file /tmp/tmpcrpzmo5l/audio.webm (pass -k to keep) loading audio... running classification heads... 2023-05-25 09:53:35.885714: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz [ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-3class.pb` [ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-3class.pb` done!Prediction
mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96IDgrnb774knbcbdnrtt63wjajprqStatusSucceededSourceWebHardwareCPUTotal durationCreatedInput
- url
- https://www.youtube.com/watch?v=jl5hJAr5paY
- model_type
- effnet-discogs-test-regression
{ "url": "https://www.youtube.com/watch?v=jl5hJAr5paY", "model_type": "effnet-discogs-test-regression" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96", { input: { url: "https://www.youtube.com/watch?v=jl5hJAr5paY", model_type: "effnet-discogs-test-regression" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96", input={ "url": "https://www.youtube.com/watch?v=jl5hJAr5paY", "model_type": "effnet-discogs-test-regression" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96", "input": { "url": "https://www.youtube.com/watch?v=jl5hJAr5paY", "model_type": "effnet-discogs-test-regression" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2023-05-25T09:56:12.667372Z", "created_at": "2023-05-25T09:56:04.556224Z", "data_removed": false, "error": null, "id": "grnb774knbcbdnrtt63wjajprq", "input": { "url": "https://www.youtube.com/watch?v=jl5hJAr5paY", "model_type": "effnet-discogs-test-regression" }, "logs": "[youtube] jl5hJAr5paY: Downloading webpage\n[dashsegments] Total fragments: 1\n[download] Destination: /tmp/tmp3n_1wce2/audio.webm\n[download] 0.0% of ~5.20MiB at 5.21KiB/s ETA 17:01\n[download] 0.1% of ~5.20MiB at 15.61KiB/s ETA 05:40\n[download] 0.1% of ~5.20MiB at 36.39KiB/s ETA 02:26\n[download] 0.3% of ~5.20MiB at 77.82KiB/s ETA 01:08\n[download] 0.6% of ~5.20MiB at 153.94KiB/s ETA 00:34\n[download] 1.2% of ~5.20MiB at 299.49KiB/s ETA 00:17\n[download] 2.4% of ~5.20MiB at 576.96KiB/s ETA 00:09\n[download] 4.8% of ~5.20MiB at 1.08MiB/s ETA 00:04\n[download] 9.6% of ~5.20MiB at 2.07MiB/s ETA 00:02\n[download] 19.2% of ~5.20MiB at 3.92MiB/s ETA 00:01\n[download] 38.5% of ~5.20MiB at 6.13MiB/s ETA 00:00\n[download] 77.0% of ~5.20MiB at 11.59MiB/s ETA 00:00\n[download] 100.0% of ~5.20MiB at 11.02MiB/s ETA 00:00\n[download] 100.0% of ~5.20MiB at 11.01MiB/s ETA 00:00\n[download] 100% of 5.20MiB in 00:00\n[ffmpeg] Destination: /tmp/tmp3n_1wce2/audio.wav\nDeleting original file /tmp/tmp3n_1wce2/audio.webm (pass -k to keep)\nloading audio...\nrunning classification heads...\n[ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-regression.pb`\n[ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-regression.pb`\ndone!", "metrics": { "predict_time": 8.175925, "total_time": 8.111148 }, "output": "https://replicate.delivery/pbxt/GhrL74u2TN7ZIlaYJ7zTQXdXZCubvqTDYyNV3Zw2p2EvizPE/out.md", "started_at": "2023-05-25T09:56:04.491447Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/grnb774knbcbdnrtt63wjajprq", "cancel": "https://api.replicate.com/v1/predictions/grnb774knbcbdnrtt63wjajprq/cancel" }, "version": "386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96" }Generated in[youtube] jl5hJAr5paY: Downloading webpage [dashsegments] Total fragments: 1 [download] Destination: /tmp/tmp3n_1wce2/audio.webm [download] 0.0% of ~5.20MiB at 5.21KiB/s ETA 17:01 [download] 0.1% of ~5.20MiB at 15.61KiB/s ETA 05:40 [download] 0.1% of ~5.20MiB at 36.39KiB/s ETA 02:26 [download] 0.3% of ~5.20MiB at 77.82KiB/s ETA 01:08 [download] 0.6% of ~5.20MiB at 153.94KiB/s ETA 00:34 [download] 1.2% of ~5.20MiB at 299.49KiB/s ETA 00:17 [download] 2.4% of ~5.20MiB at 576.96KiB/s ETA 00:09 [download] 4.8% of ~5.20MiB at 1.08MiB/s ETA 00:04 [download] 9.6% of ~5.20MiB at 2.07MiB/s ETA 00:02 [download] 19.2% of ~5.20MiB at 3.92MiB/s ETA 00:01 [download] 38.5% of ~5.20MiB at 6.13MiB/s ETA 00:00 [download] 77.0% of ~5.20MiB at 11.59MiB/s ETA 00:00 [download] 100.0% of ~5.20MiB at 11.02MiB/s ETA 00:00 [download] 100.0% of ~5.20MiB at 11.01MiB/s ETA 00:00 [download] 100% of 5.20MiB in 00:00 [ffmpeg] Destination: /tmp/tmp3n_1wce2/audio.wav Deleting original file /tmp/tmp3n_1wce2/audio.webm (pass -k to keep) loading audio... running classification heads... [ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-regression.pb` [ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-regression.pb` done!Prediction
mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97IDqy4wvv52krg5fajdsut6rpfun4StatusSucceededSourceWebHardwareCPUTotal durationCreatedInput
- url
- https://www.youtube.com/watch?v=NCtzkaL2t_Y
- model_type
- regression
{ "url": "https://www.youtube.com/watch?v=NCtzkaL2t_Y", "model_type": "regression" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", { input: { url: "https://www.youtube.com/watch?v=NCtzkaL2t_Y", model_type: "regression" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", input={ "url": "https://www.youtube.com/watch?v=NCtzkaL2t_Y", "model_type": "regression" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", "input": { "url": "https://www.youtube.com/watch?v=NCtzkaL2t_Y", "model_type": "regression" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2023-05-25T10:34:07.081923Z", "created_at": "2023-05-25T10:33:57.830339Z", "data_removed": false, "error": null, "id": "qy4wvv52krg5fajdsut6rpfun4", "input": { "url": "https://www.youtube.com/watch?v=NCtzkaL2t_Y", "model_type": "regression" }, "logs": "[youtube] NCtzkaL2t_Y: Downloading webpage\n[youtube] NCtzkaL2t_Y: Downloading player 41b8bed0\n[dashsegments] Total fragments: 1\n[download] Destination: /tmp/tmpg60jz9_g/audio.webm\n[download] 0.0% of ~3.01MiB at 14.64KiB/s ETA 03:30\n[download] 0.1% of ~3.01MiB at 43.83KiB/s ETA 01:10\n[download] 0.2% of ~3.01MiB at 102.10KiB/s ETA 00:30\n[download] 0.5% of ~3.01MiB at 217.56KiB/s ETA 00:14\n[download] 1.0% of ~3.01MiB at 399.04KiB/s ETA 00:07\n[download] 2.0% of ~3.01MiB at 729.85KiB/s ETA 00:04\n[download] 4.1% of ~3.01MiB at 1.28MiB/s ETA 00:02\n[download] 8.3% of ~3.01MiB at 2.31MiB/s ETA 00:01\n[download] 16.6% of ~3.01MiB at 4.21MiB/s ETA 00:00\n[download] 33.2% of ~3.01MiB at 7.73MiB/s ETA 00:00\n[download] 66.4% of ~3.01MiB at 14.27MiB/s ETA 00:00\n[download] 100.0% of ~3.01MiB at 20.63MiB/s ETA 00:00\n[download] 100.0% of ~3.01MiB at 20.55MiB/s ETA 00:00\n[download] 100% of 3.01MiB in 00:00\n[ffmpeg] Destination: /tmp/tmpg60jz9_g/audio.wav\nDeleting original file /tmp/tmpg60jz9_g/audio.webm (pass -k to keep)\nloading audio...\nrunning classification heads...\n2023-05-25 10:34:04.433585: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\n2023-05-25 10:34:05.445888: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 75497472 exceeds 10% of free system memory.\n2023-05-25 10:34:05.467522: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 75497472 exceeds 10% of free system memory.\n2023-05-25 10:34:05.505885: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 75497472 exceeds 10% of free system memory.\n2023-05-25 10:34:05.534400: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 81100800 exceeds 10% of free system memory.\n2023-05-25 10:34:05.552320: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 81100800 exceeds 10% of free system memory.\n[ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-regression.pb`\n[ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-regression.pb`\ndone!", "metrics": { "predict_time": 9.234996, "total_time": 9.251584 }, "output": "https://replicate.delivery/pbxt/HiCgYJxzf6z6KiUT5ehROh5sWPgXtKHZ22lzLB02uJsecdeDB/out.md", "started_at": "2023-05-25T10:33:57.846927Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/qy4wvv52krg5fajdsut6rpfun4", "cancel": "https://api.replicate.com/v1/predictions/qy4wvv52krg5fajdsut6rpfun4/cancel" }, "version": "a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97" }Generated in[youtube] NCtzkaL2t_Y: Downloading webpage [youtube] NCtzkaL2t_Y: Downloading player 41b8bed0 [dashsegments] Total fragments: 1 [download] Destination: /tmp/tmpg60jz9_g/audio.webm [download] 0.0% of ~3.01MiB at 14.64KiB/s ETA 03:30 [download] 0.1% of ~3.01MiB at 43.83KiB/s ETA 01:10 [download] 0.2% of ~3.01MiB at 102.10KiB/s ETA 00:30 [download] 0.5% of ~3.01MiB at 217.56KiB/s ETA 00:14 [download] 1.0% of ~3.01MiB at 399.04KiB/s ETA 00:07 [download] 2.0% of ~3.01MiB at 729.85KiB/s ETA 00:04 [download] 4.1% of ~3.01MiB at 1.28MiB/s ETA 00:02 [download] 8.3% of ~3.01MiB at 2.31MiB/s ETA 00:01 [download] 16.6% of ~3.01MiB at 4.21MiB/s ETA 00:00 [download] 33.2% of ~3.01MiB at 7.73MiB/s ETA 00:00 [download] 66.4% of ~3.01MiB at 14.27MiB/s ETA 00:00 [download] 100.0% of ~3.01MiB at 20.63MiB/s ETA 00:00 [download] 100.0% of ~3.01MiB at 20.55MiB/s ETA 00:00 [download] 100% of 3.01MiB in 00:00 [ffmpeg] Destination: /tmp/tmpg60jz9_g/audio.wav Deleting original file /tmp/tmpg60jz9_g/audio.webm (pass -k to keep) loading audio... running classification heads... 2023-05-25 10:34:04.433585: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz 2023-05-25 10:34:05.445888: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 75497472 exceeds 10% of free system memory. 2023-05-25 10:34:05.467522: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 75497472 exceeds 10% of free system memory. 2023-05-25 10:34:05.505885: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 75497472 exceeds 10% of free system memory. 2023-05-25 10:34:05.534400: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 81100800 exceeds 10% of free system memory. 2023-05-25 10:34:05.552320: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 81100800 exceeds 10% of free system memory. [ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-regression.pb` [ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-regression.pb` done!Prediction
mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97ID5s7pvtecx5ef5pgd6yiy6q224iStatusSucceededSourceWebHardwareCPUTotal durationCreatedInput
- url
- https://www.youtube.com/watch?v=HQmmM_qwG4k
- model_type
- regression
{ "url": "https://www.youtube.com/watch?v=HQmmM_qwG4k", "model_type": "regression" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", { input: { url: "https://www.youtube.com/watch?v=HQmmM_qwG4k", model_type: "regression" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", input={ "url": "https://www.youtube.com/watch?v=HQmmM_qwG4k", "model_type": "regression" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", "input": { "url": "https://www.youtube.com/watch?v=HQmmM_qwG4k", "model_type": "regression" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2023-05-25T10:36:01.619835Z", "created_at": "2023-05-25T10:35:50.815508Z", "data_removed": false, "error": null, "id": "5s7pvtecx5ef5pgd6yiy6q224i", "input": { "url": "https://www.youtube.com/watch?v=HQmmM_qwG4k", "model_type": "regression" }, "logs": "[youtube] HQmmM_qwG4k: Downloading webpage\n[dashsegments] Total fragments: 1\n[download] Destination: /tmp/tmp0rcuy725/audio.webm\n[download] 0.0% of ~4.42MiB at 14.73KiB/s ETA 05:07\n[download] 0.1% of ~4.42MiB at 44.06KiB/s ETA 01:42\n[download] 0.2% of ~4.42MiB at 102.14KiB/s ETA 00:44\n[download] 0.3% of ~4.42MiB at 217.46KiB/s ETA 00:20\n[download] 0.7% of ~4.42MiB at 401.18KiB/s ETA 00:11\n[download] 1.4% of ~4.42MiB at 733.83KiB/s ETA 00:06\n[download] 2.8% of ~4.42MiB at 1.28MiB/s ETA 00:03\n[download] 5.6% of ~4.42MiB at 2.32MiB/s ETA 00:01\n[download] 11.3% of ~4.42MiB at 4.24MiB/s ETA 00:00\n[download] 22.6% of ~4.42MiB at 7.77MiB/s ETA 00:00\n[download] 45.2% of ~4.42MiB at 14.33MiB/s ETA 00:00\n[download] 90.4% of ~4.42MiB at 26.49MiB/s ETA 00:00\n[download] 100.0% of ~4.42MiB at 28.94MiB/s ETA 00:00\n[download] 100.0% of ~4.42MiB at 28.88MiB/s ETA 00:00\n[download] 100% of 4.42MiB in 00:00\n[ffmpeg] Destination: /tmp/tmp0rcuy725/audio.wav\nDeleting original file /tmp/tmp0rcuy725/audio.webm (pass -k to keep)\nloading audio...\nrunning classification heads...\ndone!", "metrics": { "predict_time": 10.825566, "total_time": 10.804327 }, "output": "https://replicate.delivery/pbxt/drRGnk2qjG6yJhY5Ne1zMQUI5bB5i93vOrrR8dWBGUyIYnfQA/out.md", "started_at": "2023-05-25T10:35:50.794269Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5s7pvtecx5ef5pgd6yiy6q224i", "cancel": "https://api.replicate.com/v1/predictions/5s7pvtecx5ef5pgd6yiy6q224i/cancel" }, "version": "a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97" }Generated in[youtube] HQmmM_qwG4k: Downloading webpage [dashsegments] Total fragments: 1 [download] Destination: /tmp/tmp0rcuy725/audio.webm [download] 0.0% of ~4.42MiB at 14.73KiB/s ETA 05:07 [download] 0.1% of ~4.42MiB at 44.06KiB/s ETA 01:42 [download] 0.2% of ~4.42MiB at 102.14KiB/s ETA 00:44 [download] 0.3% of ~4.42MiB at 217.46KiB/s ETA 00:20 [download] 0.7% of ~4.42MiB at 401.18KiB/s ETA 00:11 [download] 1.4% of ~4.42MiB at 733.83KiB/s ETA 00:06 [download] 2.8% of ~4.42MiB at 1.28MiB/s ETA 00:03 [download] 5.6% of ~4.42MiB at 2.32MiB/s ETA 00:01 [download] 11.3% of ~4.42MiB at 4.24MiB/s ETA 00:00 [download] 22.6% of ~4.42MiB at 7.77MiB/s ETA 00:00 [download] 45.2% of ~4.42MiB at 14.33MiB/s ETA 00:00 [download] 90.4% of ~4.42MiB at 26.49MiB/s ETA 00:00 [download] 100.0% of ~4.42MiB at 28.94MiB/s ETA 00:00 [download] 100.0% of ~4.42MiB at 28.88MiB/s ETA 00:00 [download] 100% of 4.42MiB in 00:00 [ffmpeg] Destination: /tmp/tmp0rcuy725/audio.wav Deleting original file /tmp/tmp0rcuy725/audio.webm (pass -k to keep) loading audio... running classification heads... done!Prediction
mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97IDfw5w4a7xh5a6vidqyu33y6et3iStatusSucceededSourceWebHardwareCPUTotal durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%00:00:000Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- model_type
- 2 classes
{ "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", "model_type": "2 classes" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", { input: { audio: "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", model_type: "2 classes" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", input={ "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", "model_type": "2 classes" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", "input": { "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", "model_type": "2 classes" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2023-05-25T10:38:50.933346Z", "created_at": "2023-05-25T10:38:45.484927Z", "data_removed": false, "error": null, "id": "fw5w4a7xh5a6vidqyu33y6et3i", "input": { "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3", "model_type": "2 classes" }, "logs": "loading audio...\nrunning classification heads...\n[ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-2class.pb`\n[ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-2class.pb`\ndone!", "metrics": { "predict_time": 5.508027, "total_time": 5.448419 }, "output": "https://replicate.delivery/pbxt/HSePfdMxmGvz00quRIWOw8YQHMPEg6g2CnVYNUx9HsB6yOfhA/out.md", "started_at": "2023-05-25T10:38:45.425319Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fw5w4a7xh5a6vidqyu33y6et3i", "cancel": "https://api.replicate.com/v1/predictions/fw5w4a7xh5a6vidqyu33y6et3i/cancel" }, "version": "a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97" }Generated inloading audio... running classification heads... [ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-2class.pb` [ INFO ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-2class.pb` done!Prediction
mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97IDatazkq7gmrabjeikmcgmkt3xviStatusSucceededSourceWebHardwareCPUTotal durationCreatedInput
- url
- https://www.youtube.com/watch?v=L-iepu3EtyE
- model_type
- regression
{ "url": "https://www.youtube.com/watch?v=L-iepu3EtyE", "model_type": "regression" }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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", { input: { url: "https://www.youtube.com/watch?v=L-iepu3EtyE", model_type: "regression" } } ); // 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", input={ "url": "https://www.youtube.com/watch?v=L-iepu3EtyE", "model_type": "regression" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97", "input": { "url": "https://www.youtube.com/watch?v=L-iepu3EtyE", "model_type": "regression" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2023-05-25T10:41:07.567807Z", "created_at": "2023-05-25T10:41:00.505945Z", "data_removed": false, "error": null, "id": "atazkq7gmrabjeikmcgmkt3xvi", "input": { "url": "https://www.youtube.com/watch?v=L-iepu3EtyE", "model_type": "regression" }, "logs": "[youtube] L-iepu3EtyE: Downloading webpage\n[dashsegments] Total fragments: 1\n[download] Destination: /tmp/tmprc_j2w60/audio.webm\n[download] 0.0% of ~3.84MiB at 16.07KiB/s ETA 04:04\n[download] 0.1% of ~3.84MiB at 48.07KiB/s ETA 01:21\n[download] 0.2% of ~3.84MiB at 111.84KiB/s ETA 00:35\n[download] 0.4% of ~3.84MiB at 237.81KiB/s ETA 00:16\n[download] 0.8% of ~3.84MiB at 437.28KiB/s ETA 00:08\n[download] 1.6% of ~3.84MiB at 799.58KiB/s ETA 00:04\n[download] 3.2% of ~3.84MiB at 1.40MiB/s ETA 00:02\n[download] 6.5% of ~3.84MiB at 2.52MiB/s ETA 00:01\n[download] 13.0% of ~3.84MiB at 4.59MiB/s ETA 00:00\n[download] 26.0% of ~3.84MiB at 8.41MiB/s ETA 00:00\n[download] 52.1% of ~3.84MiB at 15.55MiB/s ETA 00:00\n[download] 100.0% of ~3.84MiB at 27.76MiB/s ETA 00:00\n[download] 100.0% of ~3.84MiB at 27.68MiB/s ETA 00:00\n[download] 100% of 3.84MiB in 00:00\n[ffmpeg] Destination: /tmp/tmprc_j2w60/audio.wav\nDeleting original file /tmp/tmprc_j2w60/audio.webm (pass -k to keep)\nloading audio...\nrunning classification heads...\ndone!", "metrics": { "predict_time": 7.115407, "total_time": 7.061862 }, "output": "https://replicate.delivery/pbxt/0T5Z8kCT24oVGRF1Ye9JLYVy4MyaLLL2cjbiDF58vIkhanfQA/out.md", "started_at": "2023-05-25T10:41:00.452400Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/atazkq7gmrabjeikmcgmkt3xvi", "cancel": "https://api.replicate.com/v1/predictions/atazkq7gmrabjeikmcgmkt3xvi/cancel" }, "version": "a8816edfa80405aa841c0721cc1d5f722ac949744007dd66660218b6e8933c97" }Generated in[youtube] L-iepu3EtyE: Downloading webpage [dashsegments] Total fragments: 1 [download] Destination: /tmp/tmprc_j2w60/audio.webm [download] 0.0% of ~3.84MiB at 16.07KiB/s ETA 04:04 [download] 0.1% of ~3.84MiB at 48.07KiB/s ETA 01:21 [download] 0.2% of ~3.84MiB at 111.84KiB/s ETA 00:35 [download] 0.4% of ~3.84MiB at 237.81KiB/s ETA 00:16 [download] 0.8% of ~3.84MiB at 437.28KiB/s ETA 00:08 [download] 1.6% of ~3.84MiB at 799.58KiB/s ETA 00:04 [download] 3.2% of ~3.84MiB at 1.40MiB/s ETA 00:02 [download] 6.5% of ~3.84MiB at 2.52MiB/s ETA 00:01 [download] 13.0% of ~3.84MiB at 4.59MiB/s ETA 00:00 [download] 26.0% of ~3.84MiB at 8.41MiB/s ETA 00:00 [download] 52.1% of ~3.84MiB at 15.55MiB/s ETA 00:00 [download] 100.0% of ~3.84MiB at 27.76MiB/s ETA 00:00 [download] 100.0% of ~3.84MiB at 27.68MiB/s ETA 00:00 [download] 100% of 3.84MiB in 00:00 [ffmpeg] Destination: /tmp/tmprc_j2w60/audio.wav Deleting original file /tmp/tmprc_j2w60/audio.webm (pass -k to keep) loading audio... running classification heads... done!
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