chenxwh / hart
Efficient Visual Generation with Hybrid Autoregressive Transformer
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDp7tp159kznrgp0cjm87bcknzp8StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- An astronaut riding a horse on the moon, oil painting by Van Gogh.
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "An astronaut riding a horse on the moon, oil painting by Van Gogh.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "An astronaut riding a horse on the moon, oil painting by Van Gogh.", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "An astronaut riding a horse on the moon, oil painting by Van Gogh.", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "An astronaut riding a horse on the moon, oil painting by Van Gogh.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-18T23:54:54.806502Z", "created_at": "2024-10-18T23:54:52.797000Z", "data_removed": false, "error": null, "id": "p7tp159kznrgp0cjm87bcknzp8", "input": { "prompt": "An astronaut riding a horse on the moon, oil painting by Van Gogh.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 49479", "metrics": { "predict_time": 2.001601874, "total_time": 2.009502 }, "output": "https://replicate.delivery/pbxt/Wylfq1Y7l7QDNqXSSpkmhDLk9djKCcJii8F3KxqX46CnOF0JA/out.png", "started_at": "2024-10-18T23:54:52.804900Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/p7tp159kznrgp0cjm87bcknzp8", "cancel": "https://api.replicate.com/v1/predictions/p7tp159kznrgp0cjm87bcknzp8/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDp935mvckw9rgj0cjm88trxchw8StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A dog that has been meditating all the time
- more_smooth
- guidance_scale
- 5.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "A dog that has been meditating all the time", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "A dog that has been meditating all the time", more_smooth: true, guidance_scale: 5.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "A dog that has been meditating all the time", "more_smooth": True, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "A dog that has been meditating all the time", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-18T23:58:36.020747Z", "created_at": "2024-10-18T23:58:33.954000Z", "data_removed": false, "error": null, "id": "p935mvckw9rgj0cjm88trxchw8", "input": { "prompt": "A dog that has been meditating all the time", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 62768", "metrics": { "predict_time": 2.058430806, "total_time": 2.066747 }, "output": "https://replicate.delivery/pbxt/J0SlTRypyQa6GpgnNlM3S4hYRBzpyGferYWAMRi257crgKoTA/out.png", "started_at": "2024-10-18T23:58:33.962316Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/p935mvckw9rgj0cjm88trxchw8", "cancel": "https://api.replicate.com/v1/predictions/p935mvckw9rgj0cjm88trxchw8/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDn1w9mpfv1xrgm0cjm88v9vdk20StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- neon holography crystal cat
- more_smooth
- guidance_scale
- 5.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "neon holography crystal cat", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "neon holography crystal cat", more_smooth: true, guidance_scale: 5.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "neon holography crystal cat", "more_smooth": True, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "neon holography crystal cat", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-18T23:59:02.274724Z", "created_at": "2024-10-18T23:59:00.367000Z", "data_removed": false, "error": null, "id": "n1w9mpfv1xrgm0cjm88v9vdk20", "input": { "prompt": "neon holography crystal cat", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 49859", "metrics": { "predict_time": 1.899009778, "total_time": 1.907724 }, "output": "https://replicate.delivery/pbxt/N3ie3pT2wry0RCI76O7e32uLQ32EbCTgihevZceejpdoIUBdC/out.png", "started_at": "2024-10-18T23:59:00.375714Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/n1w9mpfv1xrgm0cjm88v9vdk20", "cancel": "https://api.replicate.com/v1/predictions/n1w9mpfv1xrgm0cjm88v9vdk20/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDsajrwn2y4drgp0cjm89860nfjcStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style
- more_smooth
- guidance_scale
- 5.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", more_smooth: true, guidance_scale: 5.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", "more_smooth": True, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-18T23:59:27.788084Z", "created_at": "2024-10-18T23:59:25.731000Z", "data_removed": false, "error": null, "id": "sajrwn2y4drgp0cjm89860nfjc", "input": { "prompt": "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 9126", "metrics": { "predict_time": 2.047207247, "total_time": 2.057084 }, "output": "https://replicate.delivery/pbxt/EO6RfH1V5K1TNKHV1gllOz2bnhoWIvb6l2MhQkdD2g9vQF0JA/out.png", "started_at": "2024-10-18T23:59:25.740877Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/sajrwn2y4drgp0cjm89860nfjc", "cancel": "https://api.replicate.com/v1/predictions/sajrwn2y4drgp0cjm89860nfjc/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDwdm882w14hrgj0cjm89b0q2q6gStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style
- more_smooth
- guidance_scale
- 5.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", more_smooth: true, guidance_scale: 5.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", "more_smooth": True, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-18T23:59:36.698942Z", "created_at": "2024-10-18T23:59:34.692000Z", "data_removed": false, "error": null, "id": "wdm882w14hrgj0cjm89b0q2q6g", "input": { "prompt": "Steampunk makeup, in the style of vray tracing, colorful impasto, uhd image, indonesian art, fine feather details with bright red and yellow and green and pink and orange colours, intricate patterns and details, dark cyan and amber makeup. Rich colourful plumes. Victorian style", "more_smooth": true, "guidance_scale": 5.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 17194", "metrics": { "predict_time": 1.999075017, "total_time": 2.006942 }, "output": "https://replicate.delivery/pbxt/Bic7eCARIkVBJitroYxnFLVUjo9le6ONZe4Wq94KeyBhGqgOB/out.png", "started_at": "2024-10-18T23:59:34.699867Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/wdm882w14hrgj0cjm89b0q2q6g", "cancel": "https://api.replicate.com/v1/predictions/wdm882w14hrgj0cjm89b0q2q6g/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDbykv0nmkt9rgm0cjm8a8a95rdcStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- 8k uhd A man looks up at the starry sky, lonely and ethereal, Minimalism, Chaotic composition Op Art
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "8k uhd A man looks up at the starry sky, lonely and ethereal, Minimalism, Chaotic composition Op Art", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "8k uhd A man looks up at the starry sky, lonely and ethereal, Minimalism, Chaotic composition Op Art", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "8k uhd A man looks up at the starry sky, lonely and ethereal, Minimalism, Chaotic composition Op Art", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "8k uhd A man looks up at the starry sky, lonely and ethereal, Minimalism, Chaotic composition Op Art", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:01:52.737048Z", "created_at": "2024-10-19T00:01:50.546000Z", "data_removed": false, "error": null, "id": "bykv0nmkt9rgm0cjm8a8a95rdc", "input": { "prompt": "8k uhd A man looks up at the starry sky, lonely and ethereal, Minimalism, Chaotic composition Op Art", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 9624", "metrics": { "predict_time": 2.181176008, "total_time": 2.191048 }, "output": "https://replicate.delivery/pbxt/gkQdSR5iBFpTIJwn808Fe2sQDS0JwFbVU0RolVJe7fchHVQnA/out.png", "started_at": "2024-10-19T00:01:50.555872Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/bykv0nmkt9rgm0cjm8a8a95rdc", "cancel": "https://api.replicate.com/v1/predictions/bykv0nmkt9rgm0cjm8a8a95rdc/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDmq6pmcws95rgj0cjm8arbh5nv0StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- seed
- 42
- prompt
- Full body shot, a French woman, Photography, French Streets background, backlighting, rim light, Fujifilm.
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "seed": 42, "prompt": "Full body shot, a French woman, Photography, French Streets background, backlighting, rim light, Fujifilm.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { seed: 42, prompt: "Full body shot, a French woman, Photography, French Streets background, backlighting, rim light, Fujifilm.", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "seed": 42, "prompt": "Full body shot, a French woman, Photography, French Streets background, backlighting, rim light, Fujifilm.", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "seed": 42, "prompt": "Full body shot, a French woman, Photography, French Streets background, backlighting, rim light, Fujifilm.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:02:59.788639Z", "created_at": "2024-10-19T00:02:57.481000Z", "data_removed": false, "error": null, "id": "mq6pmcws95rgj0cjm8arbh5nv0", "input": { "seed": 42, "prompt": "Full body shot, a French woman, Photography, French Streets background, backlighting, rim light, Fujifilm.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 42", "metrics": { "predict_time": 2.298542408, "total_time": 2.307639 }, "output": "https://replicate.delivery/pbxt/JcYen4nePioKfpDaboR3cDxvSI73JG8rCIaI74uhF0DmJVQnA/out.png", "started_at": "2024-10-19T00:02:57.490097Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mq6pmcws95rgj0cjm8arbh5nv0", "cancel": "https://api.replicate.com/v1/predictions/mq6pmcws95rgj0cjm8arbh5nv0/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caID261yk6wgx1rgm0cjm8ebyjy9ncStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- melting apple on a plate
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "melting apple on a plate", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "melting apple on a plate", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "melting apple on a plate", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "melting apple on a plate", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:10:36.337106Z", "created_at": "2024-10-19T00:10:34.088000Z", "data_removed": false, "error": null, "id": "261yk6wgx1rgm0cjm8ebyjy9nc", "input": { "prompt": "melting apple on a plate", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 53152", "metrics": { "predict_time": 2.241268305, "total_time": 2.249106 }, "output": "https://replicate.delivery/pbxt/l4WYXOrVT67yIJqlrxUqXRLkUTXjXlqGvlhP7gc2J48eVF0JA/out.png", "started_at": "2024-10-19T00:10:34.095838Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/261yk6wgx1rgm0cjm8ebyjy9nc", "cancel": "https://api.replicate.com/v1/predictions/261yk6wgx1rgm0cjm8ebyjy9nc/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caID69r3j7e5knrgg0cjm8fs6faaq8StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A small cactus with a happy face in the Sahara desert
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "A small cactus with a happy face in the Sahara desert", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "A small cactus with a happy face in the Sahara desert", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "A small cactus with a happy face in the Sahara desert", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "A small cactus with a happy face in the Sahara desert", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:14:06.440969Z", "created_at": "2024-10-19T00:14:04.189000Z", "data_removed": false, "error": null, "id": "69r3j7e5knrgg0cjm8fs6faaq8", "input": { "prompt": "A small cactus with a happy face in the Sahara desert", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 51637", "metrics": { "predict_time": 2.233373652, "total_time": 2.251969 }, "output": "https://replicate.delivery/pbxt/PIiOkydVBJZMEBvMyf9cCEchewYV2fmuOlTJAtgymAHaeqgOB/out.png", "started_at": "2024-10-19T00:14:04.207595Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/69r3j7e5knrgg0cjm8fs6faaq8", "cancel": "https://api.replicate.com/v1/predictions/69r3j7e5knrgg0cjm8fs6faaq8/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDvah4d56g1hrgj0cjm8g9yv64hrStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A panda that has been cybernetically enhanced.
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "A panda that has been cybernetically enhanced.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "A panda that has been cybernetically enhanced.", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "A panda that has been cybernetically enhanced.", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "A panda that has been cybernetically enhanced.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:15:14.478216Z", "created_at": "2024-10-19T00:15:12.396000Z", "data_removed": false, "error": null, "id": "vah4d56g1hrgj0cjm8g9yv64hr", "input": { "prompt": "A panda that has been cybernetically enhanced.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 18754", "metrics": { "predict_time": 2.073196801, "total_time": 2.082216 }, "output": "https://replicate.delivery/pbxt/X7hlj8vsBl6iHlEcKk3NyhdfYhHlcJmrt8gZiVlFct3IYF0JA/out.png", "started_at": "2024-10-19T00:15:12.405019Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vah4d56g1hrgj0cjm8g9yv64hr", "cancel": "https://api.replicate.com/v1/predictions/vah4d56g1hrgj0cjm8g9yv64hr/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caID10f9nkq1ehrgm0cjm8gtv3wph4StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A lighthouse in a giant wave, origami style
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "A lighthouse in a giant wave, origami style", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "A lighthouse in a giant wave, origami style", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "A lighthouse in a giant wave, origami style", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "A lighthouse in a giant wave, origami style", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:16:24.577446Z", "created_at": "2024-10-19T00:16:22.388000Z", "data_removed": false, "error": null, "id": "10f9nkq1ehrgm0cjm8gtv3wph4", "input": { "prompt": "A lighthouse in a giant wave, origami style", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 47514", "metrics": { "predict_time": 2.181722115, "total_time": 2.189446 }, "output": "https://replicate.delivery/pbxt/stiDxm4S8oJVOpCOAGV6sKFLuN4GNbThRylPjIqp3VOWsC6E/out.png", "started_at": "2024-10-19T00:16:22.395724Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/10f9nkq1ehrgm0cjm8gtv3wph4", "cancel": "https://api.replicate.com/v1/predictions/10f9nkq1ehrgm0cjm8gtv3wph4/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDwnftvzjd5nrgj0cjm8hbtgvg58StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A beautiful cabin in Attersee, Austria, 3d animation style.
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "A beautiful cabin in Attersee, Austria, 3d animation style.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "A beautiful cabin in Attersee, Austria, 3d animation style.", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "A beautiful cabin in Attersee, Austria, 3d animation style.", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "A beautiful cabin in Attersee, Austria, 3d animation style.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:16:52.108939Z", "created_at": "2024-10-19T00:16:49.965000Z", "data_removed": false, "error": null, "id": "wnftvzjd5nrgj0cjm8hbtgvg58", "input": { "prompt": "A beautiful cabin in Attersee, Austria, 3d animation style.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 36183", "metrics": { "predict_time": 2.137272317, "total_time": 2.143939 }, "output": "https://replicate.delivery/pbxt/jb8Jvma3DVK6O9daL3a0IJFUnjFwvmy3GqLIte4QbqfzxKoTA/out.png", "started_at": "2024-10-19T00:16:49.971666Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/wnftvzjd5nrgj0cjm8hbtgvg58", "cancel": "https://api.replicate.com/v1/predictions/wnftvzjd5nrgj0cjm8hbtgvg58/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDj5cgwxx2mxrgp0cjm8jb4a85drStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A alpaca made of colorful building blocks, cyberpunk.
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "A alpaca made of colorful building blocks, cyberpunk.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "A alpaca made of colorful building blocks, cyberpunk.", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "A alpaca made of colorful building blocks, cyberpunk.", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "A alpaca made of colorful building blocks, cyberpunk.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:19:25.046586Z", "created_at": "2024-10-19T00:19:22.919000Z", "data_removed": false, "error": null, "id": "j5cgwxx2mxrgp0cjm8jb4a85dr", "input": { "prompt": "A alpaca made of colorful building blocks, cyberpunk.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 905", "metrics": { "predict_time": 2.117714205, "total_time": 2.127586 }, "output": "https://replicate.delivery/pbxt/MkIgqc7zJLLFAVaBtbpKaoaYePgfg9VTSn2y8ZKsWjPM0KoTA/out.png", "started_at": "2024-10-19T00:19:22.928872Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/j5cgwxx2mxrgp0cjm8jb4a85dr", "cancel": "https://api.replicate.com/v1/predictions/j5cgwxx2mxrgp0cjm8jb4a85dr/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDxtb7n58qxxrgp0cjm8kbx2h10wStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- beautiful lady, freckles, big smile, blue eyes, short ginger hair, dark makeup, wearing a floral blue vest top, soft light, dark grey background.
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "beautiful lady, freckles, big smile, blue eyes, short ginger hair, dark makeup, wearing a floral blue vest top, soft light, dark grey background.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "beautiful lady, freckles, big smile, blue eyes, short ginger hair, dark makeup, wearing a floral blue vest top, soft light, dark grey background.", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "beautiful lady, freckles, big smile, blue eyes, short ginger hair, dark makeup, wearing a floral blue vest top, soft light, dark grey background.", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "beautiful lady, freckles, big smile, blue eyes, short ginger hair, dark makeup, wearing a floral blue vest top, soft light, dark grey background.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:21:00.671075Z", "created_at": "2024-10-19T00:20:58.479000Z", "data_removed": false, "error": null, "id": "xtb7n58qxxrgp0cjm8kbx2h10w", "input": { "prompt": "beautiful lady, freckles, big smile, blue eyes, short ginger hair, dark makeup, wearing a floral blue vest top, soft light, dark grey background.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 55458", "metrics": { "predict_time": 2.183077313, "total_time": 2.192075 }, "output": "https://replicate.delivery/pbxt/wk7IjmjOJFauOJajhWIDFHds7rahzFG4okr2aIm25rAbtC6E/out.png", "started_at": "2024-10-19T00:20:58.487997Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xtb7n58qxxrgp0cjm8kbx2h10w", "cancel": "https://api.replicate.com/v1/predictions/xtb7n58qxxrgp0cjm8kbx2h10w/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDa8b8cec1bhrgp0cjm8kbxdm6nmStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:21:27.710408Z", "created_at": "2024-10-19T00:21:25.468000Z", "data_removed": false, "error": null, "id": "a8b8cec1bhrgp0cjm8kbxdm6nm", "input": { "prompt": "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 28836", "metrics": { "predict_time": 2.228351438, "total_time": 2.242408 }, "output": "https://replicate.delivery/pbxt/nkntvZwR7GLGJ5iyfCQBhfczdc4r44fCrXj1huRAhhrOsVQnA/out.png", "started_at": "2024-10-19T00:21:25.482056Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/a8b8cec1bhrgp0cjm8kbxdm6nm", "cancel": "https://api.replicate.com/v1/predictions/a8b8cec1bhrgp0cjm8kbxdm6nm/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
Prediction
chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073caIDtnnjf5zfk5rgg0cjm8k9p9vkd8StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.
- more_smooth
- guidance_scale
- 4.5
- max_token_length
- 300
- use_llm_system_prompt
{ "prompt": "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", { input: { prompt: "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", more_smooth: true, guidance_scale: 4.5, max_token_length: 300, use_llm_system_prompt: true } } ); // 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 replicate
Import the client:import replicate
Run chenxwh/hart using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", input={ "prompt": "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", "more_smooth": True, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": True } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())
To learn more, take a look at the guide on getting started with Python.
Run chenxwh/hart 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": "chenxwh/hart:2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca", "input": { "prompt": "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-19T00:21:55.944846Z", "created_at": "2024-10-19T00:21:53.689000Z", "data_removed": false, "error": null, "id": "tnnjf5zfk5rgg0cjm8k9p9vkd8", "input": { "prompt": "A close-up photo of a person. The subject is a woman. She wore a blue coat with a gray dress underneath. She has blue eyes and blond hair, and wears a pair of earrings. Behind are blurred city buildings and streets.", "more_smooth": true, "guidance_scale": 4.5, "max_token_length": 300, "use_llm_system_prompt": true }, "logs": "Using seed: 12813", "metrics": { "predict_time": 2.24201649, "total_time": 2.255846 }, "output": "https://replicate.delivery/pbxt/R8wi7IwEC0ZLI1OmeDnCqqBj5rT8FUufrAVP0y5nW0bj2KoTA/out.png", "started_at": "2024-10-19T00:21:53.702829Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tnnjf5zfk5rgg0cjm8k9p9vkd8", "cancel": "https://api.replicate.com/v1/predictions/tnnjf5zfk5rgg0cjm8k9p9vkd8/cancel" }, "version": "2984186483a0e1021efd42553d649f3aaa09cf7dc08e268617646bb68f1073ca" }
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