jingyunliang / hcflow-sr
Image Super-Resolution
Prediction
jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9eInput
{ "image": "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png", "model_type": "celeb" }
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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", { input: { image: "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png", model_type: "celeb" } } ); 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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", input={ "image": "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png", "model_type": "celeb" } ) # The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", "input": { "image": "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png", "model_type": "celeb" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2021-09-11T19:35:37.337732Z", "created_at": "2021-09-11T19:35:35.591027Z", "data_removed": false, "error": null, "id": "djlzjw76zvgqpl7pe5fq3daf5e", "input": { "image": "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png", "model_type": "celeb" }, "logs": null, "metrics": { "total_time": 1.746705 }, "output": [ { "file": "https://replicate.delivery/mgxm/88ee0f71-4356-4c77-9af4-58fcd21d3847/out.png" } ], "started_at": "2022-02-14T08:01:24.538842Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/djlzjw76zvgqpl7pe5fq3daf5e", "cancel": "https://api.replicate.com/v1/predictions/djlzjw76zvgqpl7pe5fq3daf5e/cancel" }, "version": "097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e" }
Prediction
jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9eInput
{ "image": "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png", "model_type": "celeb" }
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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", { input: { image: "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png", model_type: "celeb" } } ); 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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", input={ "image": "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png", "model_type": "celeb" } ) # The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", "input": { "image": "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png", "model_type": "celeb" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2021-09-11T19:35:49.005647Z", "created_at": "2021-09-11T19:35:47.322022Z", "data_removed": false, "error": null, "id": "nodd7572kjgnnnfctamhvb7u7m", "input": { "image": "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png", "model_type": "celeb" }, "logs": null, "metrics": { "total_time": 1.683625 }, "output": [ { "file": "https://replicate.delivery/mgxm/564f731e-8b53-4502-b0d7-41d01a155e6a/out.png" } ], "started_at": "2023-02-05T05:53:13.563460Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nodd7572kjgnnnfctamhvb7u7m", "cancel": "https://api.replicate.com/v1/predictions/nodd7572kjgnnnfctamhvb7u7m/cancel" }, "version": "097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e" }
Prediction
jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9eInput
{ "image": "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png", "model_type": "celeb" }
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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", { input: { image: "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png", model_type: "celeb" } } ); 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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", input={ "image": "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png", "model_type": "celeb" } ) # The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", "input": { "image": "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png", "model_type": "celeb" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2021-09-11T19:35:58.962108Z", "created_at": "2021-09-11T19:35:57.220911Z", "data_removed": false, "error": null, "id": "eug4gtwtrnb4royjzg24l3nrle", "input": { "image": "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png", "model_type": "celeb" }, "logs": null, "metrics": { "total_time": 1.741197 }, "output": [ { "file": "https://replicate.delivery/mgxm/85533735-5bd6-4832-9678-63e80963b519/out.png" } ], "started_at": "2023-01-17T13:18:41.114687Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/eug4gtwtrnb4royjzg24l3nrle", "cancel": "https://api.replicate.com/v1/predictions/eug4gtwtrnb4royjzg24l3nrle/cancel" }, "version": "097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e" }
Prediction
jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9eInput
{ "image": "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png", "model_type": "celeb" }
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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", { input: { image: "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png", model_type: "celeb" } } ); 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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", input={ "image": "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png", "model_type": "celeb" } ) # The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", "input": { "image": "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png", "model_type": "celeb" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2021-09-11T19:36:09.334330Z", "created_at": "2021-09-11T19:36:07.717541Z", "data_removed": false, "error": null, "id": "3exzbtvdlnablcwr5dzpfkbr34", "input": { "image": "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png", "model_type": "celeb" }, "logs": null, "metrics": { "total_time": 1.616789 }, "output": [ { "file": "https://replicate.delivery/mgxm/69d56dca-1672-4184-a459-0d5847e1bab4/out.png" } ], "started_at": "2023-03-01T10:58:03.515895Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3exzbtvdlnablcwr5dzpfkbr34", "cancel": "https://api.replicate.com/v1/predictions/3exzbtvdlnablcwr5dzpfkbr34/cancel" }, "version": "097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e" }
Prediction
jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9eIDrkakzczsqbdu5mmv45bd3ray6eStatusSucceededSourceWebHardware–Total duration–CreatedInput
{ "image": "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png", "model_type": "celeb" }
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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", { input: { image: "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png", model_type: "celeb" } } ); 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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", input={ "image": "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png", "model_type": "celeb" } ) # The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", "input": { "image": "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png", "model_type": "celeb" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2021-09-11T19:36:20.582786Z", "created_at": "2021-09-11T19:36:18.915259Z", "data_removed": false, "error": null, "id": "rkakzczsqbdu5mmv45bd3ray6e", "input": { "image": "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png", "model_type": "celeb" }, "logs": null, "metrics": {}, "output": [ { "file": "https://replicate.delivery/mgxm/776ce5ee-82d1-4356-857e-a2ea6b3f299a/out.png" } ], "started_at": null, "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rkakzczsqbdu5mmv45bd3ray6e", "cancel": "https://api.replicate.com/v1/predictions/rkakzczsqbdu5mmv45bd3ray6e/cancel" }, "version": "097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e" }
Prediction
jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9eInput
{ "image": "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png", "model_type": "celeb" }
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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", { input: { image: "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png", model_type: "celeb" } } ); 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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", input={ "image": "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png", "model_type": "celeb" } ) # The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", "input": { "image": "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png", "model_type": "celeb" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2021-09-11T19:36:57.963540Z", "created_at": "2021-09-11T19:36:56.124837Z", "data_removed": false, "error": null, "id": "brfrihkqurbonoh7xxjs7isdpm", "input": { "image": "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png", "model_type": "celeb" }, "logs": null, "metrics": { "total_time": 1.838703 }, "output": [ { "file": "https://replicate.delivery/mgxm/c186c6e2-02f6-4de0-8df9-3e2ab15ef881/out.png" } ], "started_at": "2023-06-21T10:30:53.159704Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/brfrihkqurbonoh7xxjs7isdpm", "cancel": "https://api.replicate.com/v1/predictions/brfrihkqurbonoh7xxjs7isdpm/cancel" }, "version": "097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e" }
Prediction
jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9eIDveeeh5afrrhbfj6xahp6gbuevqStatusSucceededSourceWebHardware–Total duration–CreatedInput
{ "image": "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png", "model_type": "general" }
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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", { input: { image: "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png", model_type: "general" } } ); 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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", input={ "image": "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png", "model_type": "general" } ) # The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema print(item)
To learn more, take a look at the guide on getting started with Python.
Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e", "input": { "image": "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png", "model_type": "general" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
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{ "completed_at": "2021-09-11T19:37:14.091624Z", "created_at": "2021-09-11T19:37:12.424106Z", "data_removed": false, "error": null, "id": "veeeh5afrrhbfj6xahp6gbuevq", "input": { "image": "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png", "model_type": "general" }, "logs": null, "metrics": {}, "output": [ { "file": "https://replicate.delivery/mgxm/4abfd6cc-fed3-4e43-8ac3-3cb4ee612147/out.png" } ], "started_at": null, "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/veeeh5afrrhbfj6xahp6gbuevq", "cancel": "https://api.replicate.com/v1/predictions/veeeh5afrrhbfj6xahp6gbuevq/cancel" }, "version": "097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e" }
Want to make some of these yourself?
Run this model