ekgren / structureddreaming
Styledreams -- CLIP x Stylegan2
- Public
- 4.1K runs
- GitHub
Prediction
ekgren/structureddreaming:b6a248320b3a985ea4c9f0709ad1843b0ac3a320863a79d546bb9809ec6c4df4Input
- prompt
- portrait painting of neon gods by Into the Void
- iterations
- "300"
- display_frequency
- "30"
{ "prompt": "portrait painting of neon gods by Into the Void", "iterations": "300", "display_frequency": "30" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ekgren/structureddreaming:b6a248320b3a985ea4c9f0709ad1843b0ac3a320863a79d546bb9809ec6c4df4", { input: { prompt: "portrait painting of neon gods by Into the Void", iterations: "300", display_frequency: "30" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ekgren/structureddreaming:b6a248320b3a985ea4c9f0709ad1843b0ac3a320863a79d546bb9809ec6c4df4", input={ "prompt": "portrait painting of neon gods by Into the Void", "iterations": "300", "display_frequency": "30" } ) # The ekgren/structureddreaming model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/ekgren/structureddreaming/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run ekgren/structureddreaming 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": "ekgren/structureddreaming:b6a248320b3a985ea4c9f0709ad1843b0ac3a320863a79d546bb9809ec6c4df4", "input": { "prompt": "portrait painting of neon gods by Into the Void", "iterations": "300", "display_frequency": "30" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-10-05T21:41:00.795314Z", "created_at": "2021-10-05T21:37:18.213030Z", "data_removed": false, "error": null, "id": "s4s6brg2tffqxlaowbqqreuju4", "input": { "prompt": "portrait painting of neon gods by Into the Void", "iterations": "300", "display_frequency": "30" }, "logs": "Generating image.\nSetting up PyTorch plugin \"bias_act_plugin\"...\nDone.\nSetting up PyTorch plugin \"upfirdn2d_plugin\"...\nDone.\nstep: 30, loss: -20.546875, img.min: -0.04773811250925064, img.max: 0.9971683621406555\nstep: 60, loss: -25.734375, img.min: -0.049006085842847824, img.max: 1.026373267173767\nstep: 90, loss: -26.46875, img.min: -0.07080622762441635, img.max: 1.0104471445083618\nstep: 120, loss: -34.125, img.min: -0.0940389633178711, img.max: 1.0469348430633545\nstep: 150, loss: -31.5, img.min: -0.1317528337240219, img.max: 1.000837802886963\nstep: 180, loss: -35.15625, img.min: -0.11546284705400467, img.max: 1.0702193975448608\nstep: 210, loss: -34.46875, img.min: -0.05544739216566086, img.max: 0.9569833278656006\nstep: 240, loss: -30.828125, img.min: -0.09335537254810333, img.max: 0.9662722945213318\nstep: 270, loss: -38.53125, img.min: -0.07021424919366837, img.max: 0.9920296669006348", "metrics": { "total_time": 222.582284 }, "output": [ { "file": "https://replicate.delivery/mgxm/b498e10e-c1d8-4f1e-bcd5-6c4bf4b29bc7/out.png" }, { "file": "https://replicate.delivery/mgxm/37b92194-1742-45c9-abe7-109fd094335d/out.png" }, { "file": "https://replicate.delivery/mgxm/8b0c81ed-b418-4b1a-8d89-4f4650b76574/out.png" }, { "file": "https://replicate.delivery/mgxm/c4ad6c52-736b-43e8-a3c8-76c4e08fef09/out.png" }, { "file": "https://replicate.delivery/mgxm/b0bf6d75-dee5-4b1f-aa30-140977d18baf/out.png" }, { "file": "https://replicate.delivery/mgxm/cd1cb97a-480c-48df-b750-6c8f0ae07c30/out.png" }, { "file": "https://replicate.delivery/mgxm/e9c79f9d-5def-4778-9057-c54883ee1b8d/out.png" }, { "file": "https://replicate.delivery/mgxm/261943fe-25be-4c4b-8eb8-d1f3f893e2d7/out.png" }, { "file": "https://replicate.delivery/mgxm/12a407bb-0374-4f8a-9141-6dedd2c2eb59/out.png" } ], "started_at": "2022-06-16T08:39:22.504610Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/s4s6brg2tffqxlaowbqqreuju4", "cancel": "https://api.replicate.com/v1/predictions/s4s6brg2tffqxlaowbqqreuju4/cancel" }, "version": "b6a248320b3a985ea4c9f0709ad1843b0ac3a320863a79d546bb9809ec6c4df4" }
Generating image. Setting up PyTorch plugin "bias_act_plugin"... Done. Setting up PyTorch plugin "upfirdn2d_plugin"... Done. step: 30, loss: -20.546875, img.min: -0.04773811250925064, img.max: 0.9971683621406555 step: 60, loss: -25.734375, img.min: -0.049006085842847824, img.max: 1.026373267173767 step: 90, loss: -26.46875, img.min: -0.07080622762441635, img.max: 1.0104471445083618 step: 120, loss: -34.125, img.min: -0.0940389633178711, img.max: 1.0469348430633545 step: 150, loss: -31.5, img.min: -0.1317528337240219, img.max: 1.000837802886963 step: 180, loss: -35.15625, img.min: -0.11546284705400467, img.max: 1.0702193975448608 step: 210, loss: -34.46875, img.min: -0.05544739216566086, img.max: 0.9569833278656006 step: 240, loss: -30.828125, img.min: -0.09335537254810333, img.max: 0.9662722945213318 step: 270, loss: -38.53125, img.min: -0.07021424919366837, img.max: 0.9920296669006348
Prediction
ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2IDud44lwx4rbaf3j3shxykdpyz7qStatusSucceededSourceWebHardware–Total duration–CreatedInput
- prompt
- portrait painting of android from dystopic future by James Gurney
- iterations
- "300"
- display_frequency
- "30"
{ "prompt": "portrait painting of android from dystopic future by James Gurney", "iterations": "300", "display_frequency": "30" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", { input: { prompt: "portrait painting of android from dystopic future by James Gurney", iterations: "300", display_frequency: "30" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", input={ "prompt": "portrait painting of android from dystopic future by James Gurney", "iterations": "300", "display_frequency": "30" } ) # The ekgren/structureddreaming model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/ekgren/structureddreaming/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run ekgren/structureddreaming 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": "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", "input": { "prompt": "portrait painting of android from dystopic future by James Gurney", "iterations": "300", "display_frequency": "30" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-10-05T22:59:04.045560Z", "created_at": "2021-10-05T22:58:01.564492Z", "data_removed": false, "error": null, "id": "ud44lwx4rbaf3j3shxykdpyz7q", "input": { "prompt": "portrait painting of android from dystopic future by James Gurney", "iterations": "300", "display_frequency": "30" }, "logs": "Generating image.\nstep: 30, loss: -21.28125, img.min: -0.027019187808036804, img.max: 1.0694260597229004\nstep: 60, loss: -30.15625, img.min: -0.015890084207057953, img.max: 1.061873435974121\nstep: 90, loss: -29.515625, img.min: 0.025324564427137375, img.max: 0.9573884010314941\nstep: 120, loss: -36.65625, img.min: -0.0055822040885686874, img.max: 1.3040475845336914\nstep: 150, loss: -30.734375, img.min: -0.22889405488967896, img.max: 1.4435911178588867\nstep: 180, loss: -29.984375, img.min: -0.007553280331194401, img.max: 1.3967899084091187\nstep: 210, loss: -35.84375, img.min: -0.03368733823299408, img.max: 1.2678558826446533\nstep: 240, loss: -32.25, img.min: -0.03167048469185829, img.max: 1.3929731845855713\nstep: 270, loss: -36.5, img.min: -0.002387551823630929, img.max: 1.3353346586227417", "metrics": {}, "output": [ { "file": "https://replicate.delivery/mgxm/fbb78f1d-19a5-4378-a242-c057dbf9bc5d/out.png" }, { "file": "https://replicate.delivery/mgxm/3c5adee9-18c5-47fa-8f43-1caf5d0e3aad/out.png" }, { "file": "https://replicate.delivery/mgxm/9dda9f96-a00b-471c-a79b-915d12a0e4cd/out.png" }, { "file": "https://replicate.delivery/mgxm/4b2c1d63-4ede-4d5b-8cac-85cbd15547a6/out.png" }, { "file": "https://replicate.delivery/mgxm/3a9ae746-e493-4876-abea-4c0978a722aa/out.png" }, { "file": "https://replicate.delivery/mgxm/06e957e2-06c1-4be2-9bb6-3b8db029d1c9/out.png" }, { "file": "https://replicate.delivery/mgxm/82d7428c-5408-4e48-9b1d-ba8d73a1565d/out.png" }, { "file": "https://replicate.delivery/mgxm/cd97b66c-ce9d-4c3b-ae98-2fad969a929c/out.png" }, { "file": "https://replicate.delivery/mgxm/88136021-fe89-4aed-bfb9-28fe7d64795b/out.png" }, { "file": "https://replicate.delivery/mgxm/bd7d5f10-1295-4b6b-a6b5-4f14aceb181b/out.png" } ], "started_at": null, "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ud44lwx4rbaf3j3shxykdpyz7q", "cancel": "https://api.replicate.com/v1/predictions/ud44lwx4rbaf3j3shxykdpyz7q/cancel" }, "version": "29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2" }
Generating image. step: 30, loss: -21.28125, img.min: -0.027019187808036804, img.max: 1.0694260597229004 step: 60, loss: -30.15625, img.min: -0.015890084207057953, img.max: 1.061873435974121 step: 90, loss: -29.515625, img.min: 0.025324564427137375, img.max: 0.9573884010314941 step: 120, loss: -36.65625, img.min: -0.0055822040885686874, img.max: 1.3040475845336914 step: 150, loss: -30.734375, img.min: -0.22889405488967896, img.max: 1.4435911178588867 step: 180, loss: -29.984375, img.min: -0.007553280331194401, img.max: 1.3967899084091187 step: 210, loss: -35.84375, img.min: -0.03368733823299408, img.max: 1.2678558826446533 step: 240, loss: -32.25, img.min: -0.03167048469185829, img.max: 1.3929731845855713 step: 270, loss: -36.5, img.min: -0.002387551823630929, img.max: 1.3353346586227417
Prediction
ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2IDcmpl35pgbvh7ndba5bgem3yvbqStatusSucceededSourceWebHardware–Total duration–CreatedInput
- prompt
- a happy folk musician in the 1960s
- iterations
- "300"
- display_frequency
- "30"
{ "prompt": "a happy folk musician in the 1960s", "iterations": "300", "display_frequency": "30" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", { input: { prompt: "a happy folk musician in the 1960s", iterations: "300", display_frequency: "30" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", input={ "prompt": "a happy folk musician in the 1960s", "iterations": "300", "display_frequency": "30" } ) # The ekgren/structureddreaming model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/ekgren/structureddreaming/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run ekgren/structureddreaming 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": "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", "input": { "prompt": "a happy folk musician in the 1960s", "iterations": "300", "display_frequency": "30" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-10-05T23:19:47.282110Z", "created_at": "2021-10-05T23:18:45.335225Z", "data_removed": false, "error": null, "id": "cmpl35pgbvh7ndba5bgem3yvbq", "input": { "prompt": "a happy folk musician in the 1960s", "iterations": "300", "display_frequency": "30" }, "logs": "Generating image.\nstep: 30, loss: -25.609375, img.min: -0.06958941370248795, img.max: 0.9747754335403442\nstep: 60, loss: -29.5625, img.min: -0.07768776267766953, img.max: 0.9109538197517395\nstep: 90, loss: -29.375, img.min: -0.1289016455411911, img.max: 0.9764280319213867\nstep: 120, loss: -30.859375, img.min: -0.20008300244808197, img.max: 1.00105619430542\nstep: 150, loss: -25.609375, img.min: -0.23293261229991913, img.max: 1.189071774482727\nstep: 180, loss: -28.171875, img.min: -0.14560948312282562, img.max: 0.8521396517753601\nstep: 210, loss: -34.5, img.min: -0.11989741027355194, img.max: 0.8771337270736694\nstep: 240, loss: -31.46875, img.min: -0.18710848689079285, img.max: 0.7424522042274475\nstep: 270, loss: -30.953125, img.min: -0.15075062215328217, img.max: 0.9049798250198364", "metrics": {}, "output": [ { "file": "https://replicate.delivery/mgxm/ab1387a7-1b98-4739-8253-11f0fb349455/out.png" }, { "file": "https://replicate.delivery/mgxm/4ee878b2-9ed1-4b2c-a483-cb3d7c950b25/out.png" }, { "file": "https://replicate.delivery/mgxm/0ccb722c-6e71-44f8-bfa6-4346a1ea9247/out.png" }, { "file": "https://replicate.delivery/mgxm/3cedceda-c4f5-44c4-be5c-873b0927cd6a/out.png" }, { "file": "https://replicate.delivery/mgxm/07c9baaa-7b19-44b3-89a8-a335dfe465dd/out.png" }, { "file": "https://replicate.delivery/mgxm/01270f09-7a1b-488a-ad3a-3c608bd0180a/out.png" }, { "file": "https://replicate.delivery/mgxm/f83716ae-b7ab-47a9-977d-92e5650112cc/out.png" }, { "file": "https://replicate.delivery/mgxm/0a5da60e-83c9-48f7-9d73-4de974f837f2/out.png" }, { "file": "https://replicate.delivery/mgxm/4372f92f-2bfc-4ed7-9989-ff7924ba00bb/out.png" } ], "started_at": null, "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/cmpl35pgbvh7ndba5bgem3yvbq", "cancel": "https://api.replicate.com/v1/predictions/cmpl35pgbvh7ndba5bgem3yvbq/cancel" }, "version": "29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2" }
Generating image. step: 30, loss: -25.609375, img.min: -0.06958941370248795, img.max: 0.9747754335403442 step: 60, loss: -29.5625, img.min: -0.07768776267766953, img.max: 0.9109538197517395 step: 90, loss: -29.375, img.min: -0.1289016455411911, img.max: 0.9764280319213867 step: 120, loss: -30.859375, img.min: -0.20008300244808197, img.max: 1.00105619430542 step: 150, loss: -25.609375, img.min: -0.23293261229991913, img.max: 1.189071774482727 step: 180, loss: -28.171875, img.min: -0.14560948312282562, img.max: 0.8521396517753601 step: 210, loss: -34.5, img.min: -0.11989741027355194, img.max: 0.8771337270736694 step: 240, loss: -31.46875, img.min: -0.18710848689079285, img.max: 0.7424522042274475 step: 270, loss: -30.953125, img.min: -0.15075062215328217, img.max: 0.9049798250198364
Prediction
ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2IDlkorx6hejnhphluqagqtiihgfyStatusSucceededSourceWebHardware–Total duration–CreatedInput
- prompt
- smiling tom cruise
- iterations
- "300"
- display_frequency
- "30"
{ "prompt": "smiling tom cruise", "iterations": "300", "display_frequency": "30" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", { input: { prompt: "smiling tom cruise", iterations: "300", display_frequency: "30" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", input={ "prompt": "smiling tom cruise", "iterations": "300", "display_frequency": "30" } ) # The ekgren/structureddreaming model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/ekgren/structureddreaming/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run ekgren/structureddreaming 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": "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", "input": { "prompt": "smiling tom cruise", "iterations": "300", "display_frequency": "30" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-10-05T23:24:24.429140Z", "created_at": "2021-10-05T23:23:20.806511Z", "data_removed": false, "error": null, "id": "lkorx6hejnhphluqagqtiihgfy", "input": { "prompt": "smiling tom cruise", "iterations": "300", "display_frequency": "30" }, "logs": "Generating image.\nstep: 30, loss: -29.90625, img.min: -0.030445534735918045, img.max: 1.0512011051177979\nstep: 60, loss: -30.5625, img.min: -0.0725352019071579, img.max: 1.053893804550171\nstep: 90, loss: -35.15625, img.min: -0.016302071511745453, img.max: 1.1197974681854248\nstep: 120, loss: -31.0625, img.min: -0.03881590813398361, img.max: 1.0451586246490479\nstep: 150, loss: -36.65625, img.min: -0.13431182503700256, img.max: 1.0767837762832642\nstep: 180, loss: -37.0, img.min: -0.2121494859457016, img.max: 1.1358882188796997\nstep: 210, loss: -36.59375, img.min: -0.14578552544116974, img.max: 1.1108040809631348\nstep: 240, loss: -42.03125, img.min: -0.20403000712394714, img.max: 1.0850212574005127\nstep: 270, loss: -37.5625, img.min: -0.10413017123937607, img.max: 1.135909080505371", "metrics": {}, "output": [ { "file": "https://replicate.delivery/mgxm/156fae7e-2755-425f-a6b1-dc8c0433682a/out.png" }, { "file": "https://replicate.delivery/mgxm/8d9354a0-80c0-40bb-8864-180174021625/out.png" }, { "file": "https://replicate.delivery/mgxm/3a2350c0-4b18-4c46-bdd1-71ea03695064/out.png" }, { "file": "https://replicate.delivery/mgxm/bc15f094-211c-4392-893d-698c9a17d5ac/out.png" }, { "file": "https://replicate.delivery/mgxm/8c4d09ec-f8bb-45da-a672-bea1aade1ef8/out.png" }, { "file": "https://replicate.delivery/mgxm/7fb6eeb4-4e38-49c7-8ca5-6a9865d7f1b8/out.png" }, { "file": "https://replicate.delivery/mgxm/837d3eee-b714-4df7-b708-474c65d2a46c/out.png" } ], "started_at": null, "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/lkorx6hejnhphluqagqtiihgfy", "cancel": "https://api.replicate.com/v1/predictions/lkorx6hejnhphluqagqtiihgfy/cancel" }, "version": "29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2" }
Generating image. step: 30, loss: -29.90625, img.min: -0.030445534735918045, img.max: 1.0512011051177979 step: 60, loss: -30.5625, img.min: -0.0725352019071579, img.max: 1.053893804550171 step: 90, loss: -35.15625, img.min: -0.016302071511745453, img.max: 1.1197974681854248 step: 120, loss: -31.0625, img.min: -0.03881590813398361, img.max: 1.0451586246490479 step: 150, loss: -36.65625, img.min: -0.13431182503700256, img.max: 1.0767837762832642 step: 180, loss: -37.0, img.min: -0.2121494859457016, img.max: 1.1358882188796997 step: 210, loss: -36.59375, img.min: -0.14578552544116974, img.max: 1.1108040809631348 step: 240, loss: -42.03125, img.min: -0.20403000712394714, img.max: 1.0850212574005127 step: 270, loss: -37.5625, img.min: -0.10413017123937607, img.max: 1.135909080505371
Prediction
ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2IDiyjrpes36nfnlefocckpytb76yStatusSucceededSourceWebHardware–Total duration–CreatedInput
- prompt
- a raver in the 90s
- iterations
- "300"
- display_frequency
- "30"
{ "prompt": "a raver in the 90s", "iterations": "300", "display_frequency": "30" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", { input: { prompt: "a raver in the 90s", iterations: "300", display_frequency: "30" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", input={ "prompt": "a raver in the 90s", "iterations": "300", "display_frequency": "30" } ) # The ekgren/structureddreaming model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/ekgren/structureddreaming/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run ekgren/structureddreaming 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": "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", "input": { "prompt": "a raver in the 90s", "iterations": "300", "display_frequency": "30" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-10-05T23:46:55.652247Z", "created_at": "2021-10-05T23:45:52.460375Z", "data_removed": false, "error": null, "id": "iyjrpes36nfnlefocckpytb76y", "input": { "prompt": "a raver in the 90s", "iterations": "300", "display_frequency": "30" }, "logs": "Generating image.\nstep: 30, loss: -21.78125, img.min: -0.01842029206454754, img.max: 1.1317110061645508\nstep: 60, loss: -29.34375, img.min: -0.03304706886410713, img.max: 1.1936172246932983\nstep: 90, loss: -27.203125, img.min: -0.0036074172239750624, img.max: 1.160881757736206\nstep: 120, loss: -24.65625, img.min: -0.0631806030869484, img.max: 1.350511074066162\nstep: 150, loss: -31.125, img.min: -0.19211900234222412, img.max: 1.3373734951019287\nstep: 180, loss: -31.546875, img.min: -0.021837960928678513, img.max: 1.4637110233306885\nstep: 210, loss: -28.515625, img.min: -0.020125985145568848, img.max: 1.4114419221878052\nstep: 240, loss: -33.59375, img.min: -0.014303529635071754, img.max: 1.4251604080200195\nstep: 270, loss: -35.96875, img.min: 0.021317996084690094, img.max: 1.5664259195327759", "metrics": { "total_time": 63.191872 }, "output": [ { "file": "https://replicate.delivery/mgxm/d1fcdb94-37f5-4605-b5af-6a9418d0afbf/out.png" }, { "file": "https://replicate.delivery/mgxm/02ddd735-f0c7-4b25-abd0-6d998d6d0c81/out.png" }, { "file": "https://replicate.delivery/mgxm/46a88c14-6d10-4ee9-bf38-c0a55b3d07f4/out.png" }, { "file": "https://replicate.delivery/mgxm/57376b40-9b06-4213-8326-c84af366e06f/out.png" }, { "file": "https://replicate.delivery/mgxm/a897e4ac-4f43-40e2-9635-b41646678956/out.png" }, { "file": "https://replicate.delivery/mgxm/61e80181-3193-4469-b0ff-09f929a2c818/out.png" }, { "file": "https://replicate.delivery/mgxm/3785caa1-7356-4813-b79b-3fd79b65ccc3/out.png" }, { "file": "https://replicate.delivery/mgxm/079195c4-297e-4431-a1ff-4b5807288199/out.png" }, { "file": "https://replicate.delivery/mgxm/69a0ef08-7d87-47ef-b935-8c7fb3b207ed/out.png" } ], "started_at": "2022-02-02T03:31:13.874634Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/iyjrpes36nfnlefocckpytb76y", "cancel": "https://api.replicate.com/v1/predictions/iyjrpes36nfnlefocckpytb76y/cancel" }, "version": "29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2" }
Generating image. step: 30, loss: -21.78125, img.min: -0.01842029206454754, img.max: 1.1317110061645508 step: 60, loss: -29.34375, img.min: -0.03304706886410713, img.max: 1.1936172246932983 step: 90, loss: -27.203125, img.min: -0.0036074172239750624, img.max: 1.160881757736206 step: 120, loss: -24.65625, img.min: -0.0631806030869484, img.max: 1.350511074066162 step: 150, loss: -31.125, img.min: -0.19211900234222412, img.max: 1.3373734951019287 step: 180, loss: -31.546875, img.min: -0.021837960928678513, img.max: 1.4637110233306885 step: 210, loss: -28.515625, img.min: -0.020125985145568848, img.max: 1.4114419221878052 step: 240, loss: -33.59375, img.min: -0.014303529635071754, img.max: 1.4251604080200195 step: 270, loss: -35.96875, img.min: 0.021317996084690094, img.max: 1.5664259195327759
Prediction
ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2ID7bgnivssxndsnekjipcngxdmnqStatusSucceededSourceWebHardware–Total duration–CreatedInput
- prompt
- a painting of an alien from the x files
- iterations
- 600
- display_frequency
- "30"
{ "prompt": "a painting of an alien from the x files", "iterations": 600, "display_frequency": "30" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", { input: { prompt: "a painting of an alien from the x files", iterations: 600, display_frequency: "30" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", input={ "prompt": "a painting of an alien from the x files", "iterations": 600, "display_frequency": "30" } ) # The ekgren/structureddreaming model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/ekgren/structureddreaming/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run ekgren/structureddreaming 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": "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", "input": { "prompt": "a painting of an alien from the x files", "iterations": 600, "display_frequency": "30" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-10-06T12:08:01.726768Z", "created_at": "2021-10-06T12:05:58.733543Z", "data_removed": false, "error": null, "id": "7bgnivssxndsnekjipcngxdmnq", "input": { "prompt": "a painting of an alien from the x files", "iterations": 600, "display_frequency": "30" }, "logs": "Generating image.\nstep: 30, loss: -18.703125, img.min: -0.036884505301713943, img.max: 1.048760175704956\nstep: 60, loss: -26.484375, img.min: -0.0034624289255589247, img.max: 0.9568887948989868\nstep: 90, loss: -29.15625, img.min: 0.02009570598602295, img.max: 0.9734178781509399\nstep: 120, loss: -32.4375, img.min: 0.0317997969686985, img.max: 0.9176439046859741\nstep: 150, loss: -32.71875, img.min: 0.05209018662571907, img.max: 0.848885715007782\nstep: 180, loss: -32.40625, img.min: 0.028729310259222984, img.max: 0.9135410189628601\nstep: 210, loss: -36.65625, img.min: 0.030535591766238213, img.max: 0.9832123517990112\nstep: 240, loss: -33.53125, img.min: 0.021809538826346397, img.max: 1.059241771697998\nstep: 270, loss: -35.21875, img.min: -0.004784318618476391, img.max: 1.0598220825195312\nstep: 300, loss: -34.3125, img.min: 0.04384646192193031, img.max: 0.8443257808685303\nstep: 330, loss: -34.8125, img.min: 0.05253131687641144, img.max: 0.7544122934341431\nstep: 360, loss: -38.09375, img.min: 0.010597200132906437, img.max: 0.755791425704956\nstep: 390, loss: -34.65625, img.min: 0.07587196677923203, img.max: 0.886535108089447\nstep: 420, loss: -39.1875, img.min: 0.040905315428972244, img.max: 0.9694762825965881\nstep: 450, loss: -37.0, img.min: 0.015485607087612152, img.max: 0.980171799659729\nstep: 480, loss: -36.625, img.min: -0.03417915105819702, img.max: 0.8652831315994263\nstep: 510, loss: -32.53125, img.min: 0.03207888454198837, img.max: 0.9844458103179932\nstep: 540, loss: -37.84375, img.min: -0.04020613431930542, img.max: 1.0009325742721558\nstep: 570, loss: -37.5, img.min: 0.053882796317338943, img.max: 1.0746525526046753", "metrics": { "total_time": 122.993225 }, "output": [ { "file": "https://replicate.delivery/mgxm/3b31cadc-358d-407d-bff2-14d955c535cc/out.png" }, { "file": "https://replicate.delivery/mgxm/77ce13cf-ee12-4803-b5a7-4de261aa395e/out.png" }, { "file": "https://replicate.delivery/mgxm/b0ceeb08-bb88-4d2f-9d78-4818ad12c392/out.png" }, { "file": "https://replicate.delivery/mgxm/a2dc9fa9-5a69-418f-9682-b63cbd1df7ee/out.png" }, { "file": "https://replicate.delivery/mgxm/18219b3b-7895-4f5f-b4a1-1d30412841ec/out.png" }, { "file": "https://replicate.delivery/mgxm/a0c21f96-0e13-4ada-8e53-ed17d00e6ccc/out.png" }, { "file": "https://replicate.delivery/mgxm/b5bec531-92ce-4e4b-bd0c-fd692ca1e6b2/out.png" }, { "file": "https://replicate.delivery/mgxm/532009c2-1609-42b0-81d8-531c92e1386a/out.png" }, { "file": "https://replicate.delivery/mgxm/2557c6be-879c-4b7a-a88a-f7a7bb02c895/out.png" }, { "file": "https://replicate.delivery/mgxm/3b50617f-bc49-4834-9a72-d595017c88be/out.png" }, { "file": "https://replicate.delivery/mgxm/b154c063-84a9-424c-b9dd-3b5dd725f48b/out.png" }, { "file": "https://replicate.delivery/mgxm/ba972671-0ea1-4785-b3ce-c27975a2207b/out.png" }, { "file": "https://replicate.delivery/mgxm/035dba29-c42b-4c43-8ec1-09b791c11ecf/out.png" }, { "file": "https://replicate.delivery/mgxm/b193997f-c3d2-44b9-a3a2-c7413bb93dc4/out.png" }, { "file": "https://replicate.delivery/mgxm/2065e082-dbf5-4097-a085-8d10b9044fa4/out.png" }, { "file": "https://replicate.delivery/mgxm/1051f882-fbc8-4dbb-8cac-ff111f2e89bb/out.png" }, { "file": "https://replicate.delivery/mgxm/c6720e7e-c3d5-4e78-a8a7-47a507c7e17d/out.png" }, { "file": "https://replicate.delivery/mgxm/59a41a4c-2c49-4b1f-ae5b-1e63e4c69934/out.png" }, { "file": "https://replicate.delivery/mgxm/be4b3716-e3e5-4e9b-9249-261dea4566bf/out.png" } ], "started_at": "2022-03-05T01:07:12.823780Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7bgnivssxndsnekjipcngxdmnq", "cancel": "https://api.replicate.com/v1/predictions/7bgnivssxndsnekjipcngxdmnq/cancel" }, "version": "29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2" }
Generating image. step: 30, loss: -18.703125, img.min: -0.036884505301713943, img.max: 1.048760175704956 step: 60, loss: -26.484375, img.min: -0.0034624289255589247, img.max: 0.9568887948989868 step: 90, loss: -29.15625, img.min: 0.02009570598602295, img.max: 0.9734178781509399 step: 120, loss: -32.4375, img.min: 0.0317997969686985, img.max: 0.9176439046859741 step: 150, loss: -32.71875, img.min: 0.05209018662571907, img.max: 0.848885715007782 step: 180, loss: -32.40625, img.min: 0.028729310259222984, img.max: 0.9135410189628601 step: 210, loss: -36.65625, img.min: 0.030535591766238213, img.max: 0.9832123517990112 step: 240, loss: -33.53125, img.min: 0.021809538826346397, img.max: 1.059241771697998 step: 270, loss: -35.21875, img.min: -0.004784318618476391, img.max: 1.0598220825195312 step: 300, loss: -34.3125, img.min: 0.04384646192193031, img.max: 0.8443257808685303 step: 330, loss: -34.8125, img.min: 0.05253131687641144, img.max: 0.7544122934341431 step: 360, loss: -38.09375, img.min: 0.010597200132906437, img.max: 0.755791425704956 step: 390, loss: -34.65625, img.min: 0.07587196677923203, img.max: 0.886535108089447 step: 420, loss: -39.1875, img.min: 0.040905315428972244, img.max: 0.9694762825965881 step: 450, loss: -37.0, img.min: 0.015485607087612152, img.max: 0.980171799659729 step: 480, loss: -36.625, img.min: -0.03417915105819702, img.max: 0.8652831315994263 step: 510, loss: -32.53125, img.min: 0.03207888454198837, img.max: 0.9844458103179932 step: 540, loss: -37.84375, img.min: -0.04020613431930542, img.max: 1.0009325742721558 step: 570, loss: -37.5, img.min: 0.053882796317338943, img.max: 1.0746525526046753
Prediction
ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2IDp6ftm3tskzcfpk72f62xyvaxmiStatusSucceededSourceWebHardware–Total duration–CreatedInput
- prompt
- portrait of Miss Marple deep in thought
- iterations
- "300"
- display_frequency
- "30"
{ "prompt": "portrait of Miss Marple deep in thought", "iterations": "300", "display_frequency": "30" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", { input: { prompt: "portrait of Miss Marple deep in thought", iterations: "300", display_frequency: "30" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run ekgren/structureddreaming using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", input={ "prompt": "portrait of Miss Marple deep in thought", "iterations": "300", "display_frequency": "30" } ) # The ekgren/structureddreaming model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/ekgren/structureddreaming/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run ekgren/structureddreaming 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": "ekgren/structureddreaming:29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2", "input": { "prompt": "portrait of Miss Marple deep in thought", "iterations": "300", "display_frequency": "30" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-10-06T13:46:43.551727Z", "created_at": "2021-10-06T13:45:38.741876Z", "data_removed": false, "error": null, "id": "p6ftm3tskzcfpk72f62xyvaxmi", "input": { "prompt": "portrait of Miss Marple deep in thought", "iterations": "300", "display_frequency": "30" }, "logs": "Generating image.\nstep: 30, loss: -19.71875, img.min: -0.05619603022933006, img.max: 0.9279561638832092\nstep: 60, loss: -20.90625, img.min: -0.17231333255767822, img.max: 1.1649008989334106\nstep: 90, loss: -30.15625, img.min: -0.16094432771205902, img.max: 0.9772025942802429\nstep: 120, loss: -29.640625, img.min: -0.24708306789398193, img.max: 1.0836249589920044\nstep: 150, loss: -28.484375, img.min: -0.21661671996116638, img.max: 1.0516413450241089\nstep: 180, loss: -30.65625, img.min: -0.2793450653553009, img.max: 0.8905160427093506\nstep: 210, loss: -30.5, img.min: -0.3350343704223633, img.max: 0.9079806208610535\nstep: 240, loss: -32.59375, img.min: -0.2635732889175415, img.max: 0.8909881114959717\nstep: 270, loss: -27.046875, img.min: -0.2897617816925049, img.max: 0.8566746711730957", "metrics": {}, "output": [ { "file": "https://replicate.delivery/mgxm/b3f6480c-0e2c-45b8-a676-429aeca64e22/out.png" }, { "file": "https://replicate.delivery/mgxm/567adc64-0078-470c-9652-1e01b347acab/out.png" }, { "file": "https://replicate.delivery/mgxm/324915ce-79df-4a83-9db3-a4067ad136e2/out.png" }, { "file": "https://replicate.delivery/mgxm/b487f132-c277-4ea4-a634-512e100b32d5/out.png" }, { "file": "https://replicate.delivery/mgxm/ff906e2d-a404-4f04-a1c5-0cd155476a51/out.png" }, { "file": "https://replicate.delivery/mgxm/7dd48b1e-daab-4d4f-9905-300062813e65/out.png" }, { "file": "https://replicate.delivery/mgxm/b87e762a-5612-4889-891f-fa2f345fb019/out.png" }, { "file": "https://replicate.delivery/mgxm/1e1dc77f-a7f6-4256-90ea-c4feedc97b39/out.png" }, { "file": "https://replicate.delivery/mgxm/ff70e0aa-dc90-45c6-bbc9-e711ad362440/out.png" } ], "started_at": null, "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/p6ftm3tskzcfpk72f62xyvaxmi", "cancel": "https://api.replicate.com/v1/predictions/p6ftm3tskzcfpk72f62xyvaxmi/cancel" }, "version": "29d1199ba3a0c6d11acb64bbcbe06f771cac37664c464335cf7a1da6db4373f2" }
Generating image. step: 30, loss: -19.71875, img.min: -0.05619603022933006, img.max: 0.9279561638832092 step: 60, loss: -20.90625, img.min: -0.17231333255767822, img.max: 1.1649008989334106 step: 90, loss: -30.15625, img.min: -0.16094432771205902, img.max: 0.9772025942802429 step: 120, loss: -29.640625, img.min: -0.24708306789398193, img.max: 1.0836249589920044 step: 150, loss: -28.484375, img.min: -0.21661671996116638, img.max: 1.0516413450241089 step: 180, loss: -30.65625, img.min: -0.2793450653553009, img.max: 0.8905160427093506 step: 210, loss: -30.5, img.min: -0.3350343704223633, img.max: 0.9079806208610535 step: 240, loss: -32.59375, img.min: -0.2635732889175415, img.max: 0.8909881114959717 step: 270, loss: -27.046875, img.min: -0.2897617816925049, img.max: 0.8566746711730957
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