nvidia
/
sana
A fast image model with wide artistic range and resolutions up to 4096x4096
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelID61p1pty049rmc0ckb2mrmtwhpwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a cyberpunk cat with a neon sign that says "Sana"
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "a cyberpunk cat with a neon sign that says \"Sana\"", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "a cyberpunk cat with a neon sign that says \\"Sana\\"", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T10:55:41.205802Z", "created_at": "2024-11-23T10:55:40.066000Z", "data_removed": false, "error": null, "id": "61p1pty049rmc0ckb2mrmtwhpw", "input": { "width": 1024, "height": 1024, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 38701\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.11it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.16it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.16it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.17it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.17it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.54it/s]", "metrics": { "predict_time": 1.132538566, "total_time": 1.139802 }, "output": "https://replicate.delivery/xezq/4QOnfN1jierLrkLVzDTtm4UyQJ1r7io4shfazPpkagdb1snnA/output.png", "started_at": "2024-11-23T10:55:40.073264Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-n5mltuyvyinoakqla2rygorfrawb7wcurwkjocm2ebogf6rrxama", "get": "https://api.replicate.com/v1/predictions/61p1pty049rmc0ckb2mrmtwhpw", "cancel": "https://api.replicate.com/v1/predictions/61p1pty049rmc0ckb2mrmtwhpw/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 38701 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.11it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.16it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.16it/s] 71%|███████ | 12/17 [00:00<00:00, 22.17it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.17it/s] 100%|██████████| 17/17 [00:00<00:00, 23.54it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelIDqt8mxzpjc9rma0ckb2n8w1m4c8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- Pirate ship trapped in a cosmic maelstrom nebula, rendered in cosmic beach whirlpool engine, volumetric lighting, spectacular, ambient lights, light pollution, cinematic atmosphere, art nouveau style, illustration art artwork by SenseiJaye, intricate detail.
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "Pirate ship trapped in a cosmic maelstrom nebula, rendered in cosmic beach whirlpool engine, volumetric lighting, spectacular, ambient lights, light pollution, cinematic atmosphere, art nouveau style, illustration art artwork by SenseiJaye, intricate detail.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "Pirate ship trapped in a cosmic maelstrom nebula, rendered in cosmic beach whirlpool engine, volumetric lighting, spectacular, ambient lights, light pollution, cinematic atmosphere, art nouveau style, illustration art artwork by SenseiJaye, intricate detail.", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "Pirate ship trapped in a cosmic maelstrom nebula, rendered in cosmic beach whirlpool engine, volumetric lighting, spectacular, ambient lights, light pollution, cinematic atmosphere, art nouveau style, illustration art artwork by SenseiJaye, intricate detail.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "Pirate ship trapped in a cosmic maelstrom nebula, rendered in cosmic beach whirlpool engine, volumetric lighting, spectacular, ambient lights, light pollution, cinematic atmosphere, art nouveau style, illustration art artwork by SenseiJaye, intricate detail.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T10:56:51.490456Z", "created_at": "2024-11-23T10:56:50.274000Z", "data_removed": false, "error": null, "id": "qt8mxzpjc9rma0ckb2n8w1m4c8", "input": { "width": 1024, "height": 1024, "prompt": "Pirate ship trapped in a cosmic maelstrom nebula, rendered in cosmic beach whirlpool engine, volumetric lighting, spectacular, ambient lights, light pollution, cinematic atmosphere, art nouveau style, illustration art artwork by SenseiJaye, intricate detail.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 44675\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.14it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.12it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.10it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.11it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.07it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.47it/s]", "metrics": { "predict_time": 1.2101352730000001, "total_time": 1.216456 }, "output": "https://replicate.delivery/xezq/BqRpu3lRky4jEd3WGfUUwEKojj2UuSFPzdj9KbK8yffn3snnA/output.png", "started_at": "2024-11-23T10:56:50.280320Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-akb4ndhlggrifmg53vmp6ztkziixo4j2t3erwhdiefgy5afcyg2q", "get": "https://api.replicate.com/v1/predictions/qt8mxzpjc9rma0ckb2n8w1m4c8", "cancel": "https://api.replicate.com/v1/predictions/qt8mxzpjc9rma0ckb2n8w1m4c8/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 44675 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.14it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.12it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.10it/s] 71%|███████ | 12/17 [00:00<00:00, 22.11it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.07it/s] 100%|██████████| 17/17 [00:00<00:00, 23.47it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelIDd65aq1egedrmc0ckb2ntbrv9twStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- portrait photo of a girl, photograph, highly detailed face, depth of field
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "portrait photo of a girl, photograph, highly detailed face, depth of field", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "portrait photo of a girl, photograph, highly detailed face, depth of field", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "portrait photo of a girl, photograph, highly detailed face, depth of field", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "portrait photo of a girl, photograph, highly detailed face, depth of field", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T10:57:56.561431Z", "created_at": "2024-11-23T10:57:55.315000Z", "data_removed": false, "error": null, "id": "d65aq1egedrmc0ckb2ntbrv9tw", "input": { "width": 1024, "height": 1024, "prompt": "portrait photo of a girl, photograph, highly detailed face, depth of field", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 31591\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.15it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.13it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.14it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.13it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.13it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.51it/s]", "metrics": { "predict_time": 1.238947937, "total_time": 1.246431 }, "output": "https://replicate.delivery/xezq/Dg2EjNVlR6LWBl2JErElez98E4C8aQv3eWUxgKfAj1Gp5snnA/output.png", "started_at": "2024-11-23T10:57:55.322483Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-r7ixtxa2gj44mqcso3g6csznyhwiwdxt7fasbugahtaui53dywya", "get": "https://api.replicate.com/v1/predictions/d65aq1egedrmc0ckb2ntbrv9tw", "cancel": "https://api.replicate.com/v1/predictions/d65aq1egedrmc0ckb2ntbrv9tw/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 31591 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.15it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.13it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.14it/s] 71%|███████ | 12/17 [00:00<00:00, 22.13it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.13it/s] 100%|██████████| 17/17 [00:00<00:00, 23.51it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelID2q3n46nggsrm80ckb2pbeas5wcStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- make me a logo that says "So Fast" with a really cool flying dragon shape with lightning sparks all over the sides and all of it contains Indonesian language
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "make me a logo that says \"So Fast\" with a really cool flying dragon shape with lightning sparks all over the sides and all of it contains Indonesian language", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "make me a logo that says \"So Fast\" with a really cool flying dragon shape with lightning sparks all over the sides and all of it contains Indonesian language", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "make me a logo that says \"So Fast\" with a really cool flying dragon shape with lightning sparks all over the sides and all of it contains Indonesian language", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "make me a logo that says \\"So Fast\\" with a really cool flying dragon shape with lightning sparks all over the sides and all of it contains Indonesian language", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T10:58:53.672943Z", "created_at": "2024-11-23T10:58:52.678000Z", "data_removed": false, "error": null, "id": "2q3n46nggsrm80ckb2pbeas5wc", "input": { "width": 1024, "height": 1024, "prompt": "make me a logo that says \"So Fast\" with a really cool flying dragon shape with lightning sparks all over the sides and all of it contains Indonesian language", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 31189\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.12it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.04it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.09it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.07it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.04it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.42it/s]", "metrics": { "predict_time": 0.989245282, "total_time": 0.994943 }, "output": "https://replicate.delivery/xezq/8fydoF6fnhtulEKcQk0plNtveywPH3snkFOyhArDTZe02ZPPB/output.png", "started_at": "2024-11-23T10:58:52.683698Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-ootmml4p5vmbwptz4yi3vgy5gsoioai4dhnln36vuxvgdbyx3nta", "get": "https://api.replicate.com/v1/predictions/2q3n46nggsrm80ckb2pbeas5wc", "cancel": "https://api.replicate.com/v1/predictions/2q3n46nggsrm80ckb2pbeas5wc/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 31189 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.12it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.04it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.09it/s] 71%|███████ | 12/17 [00:00<00:00, 22.07it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.04it/s] 100%|██████████| 17/17 [00:00<00:00, 23.42it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelID2zt53gvr15rme0ckb2r8qnrqcmStatusSucceededSourceWebHardwareH100Total durationCreatedby @chenxwhInput
- width
- 1024
- height
- 1024
- prompt
- 👧 with 🌹 in the ❄️
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "👧 with 🌹 in the ❄️", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "👧 with 🌹 in the ❄️", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "👧 with 🌹 in the ❄️", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "👧 with 🌹 in the ❄️", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T11:03:01.534164Z", "created_at": "2024-11-23T11:03:00.361000Z", "data_removed": false, "error": null, "id": "2zt53gvr15rme0ckb2r8qnrqcm", "input": { "width": 1024, "height": 1024, "prompt": "👧 with 🌹 in the ❄️", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 38933\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.15it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.16it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.15it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.15it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.14it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.52it/s]", "metrics": { "predict_time": 1.166179517, "total_time": 1.173164 }, "output": "https://replicate.delivery/xezq/yF1Mul5UQCbbO5KXeNyJp4avsj5Hr9xWZpvPPhfNXsylh2zTA/output.png", "started_at": "2024-11-23T11:03:00.367984Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-o7s6prpede2jozlqq4pnwjyvt622fzp6j6etydva3caoipbxgxbq", "get": "https://api.replicate.com/v1/predictions/2zt53gvr15rme0ckb2r8qnrqcm", "cancel": "https://api.replicate.com/v1/predictions/2zt53gvr15rme0ckb2r8qnrqcm/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 38933 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.15it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.16it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.15it/s] 71%|███████ | 12/17 [00:00<00:00, 22.15it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.14it/s] 100%|██████████| 17/17 [00:00<00:00, 23.52it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelID8hn2381r3nrme0ckb2rvq5v45wStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- 🐶 Wearing 🕶 flying on the 🌈
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "🐶 Wearing 🕶 flying on the 🌈", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "🐶 Wearing 🕶 flying on the 🌈", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "🐶 Wearing 🕶 flying on the 🌈", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "🐶 Wearing 🕶 flying on the 🌈", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T11:03:50.758976Z", "created_at": "2024-11-23T11:03:49.533000Z", "data_removed": false, "error": null, "id": "8hn2381r3nrme0ckb2rvq5v45w", "input": { "width": 1024, "height": 1024, "prompt": "🐶 Wearing 🕶 flying on the 🌈", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 958\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.14it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.13it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.13it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.14it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.12it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.50it/s]", "metrics": { "predict_time": 1.218118133, "total_time": 1.225976 }, "output": "https://replicate.delivery/xezq/m9NeiSk2ofpgHUEg9deyfgLJFPMbcBoQIQkWeFD0v7F0S0e8E/output.png", "started_at": "2024-11-23T11:03:49.540858Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-xbewzmba6ocfhunz2w7dodmuw2ia6cm6nncprh5jztbnwuc2735a", "get": "https://api.replicate.com/v1/predictions/8hn2381r3nrme0ckb2rvq5v45w", "cancel": "https://api.replicate.com/v1/predictions/8hn2381r3nrme0ckb2rvq5v45w/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 958 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.14it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.13it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.13it/s] 71%|███████ | 12/17 [00:00<00:00, 22.14it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.12it/s] 100%|██████████| 17/17 [00:00<00:00, 23.50it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelIDh9pm70ywa5rma0ckb2rtec935rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- an old rusted robot wearing pants and a jacket riding skis in a supermarket.
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T11:04:32.756434Z", "created_at": "2024-11-23T11:04:31.569000Z", "data_removed": false, "error": null, "id": "h9pm70ywa5rma0ckb2rtec935r", "input": { "width": 1024, "height": 1024, "prompt": "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 15023\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.19it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.17it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.15it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.13it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.12it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.51it/s]", "metrics": { "predict_time": 1.180938113, "total_time": 1.187434 }, "output": "https://replicate.delivery/xezq/EhyTRDifM7xfT0awPXMznpdrrsrkAl3Q4NIjEVtxiRVAj2zTA/output.png", "started_at": "2024-11-23T11:04:31.575496Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-sf4gkzdr7dx6m5qyhvy2isku42u2h7jbp7knwogygyczjyg7n2za", "get": "https://api.replicate.com/v1/predictions/h9pm70ywa5rma0ckb2rtec935r", "cancel": "https://api.replicate.com/v1/predictions/h9pm70ywa5rma0ckb2rtec935r/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 15023 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.19it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.17it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.15it/s] 71%|███████ | 12/17 [00:00<00:00, 22.13it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.12it/s] 100%|██████████| 17/17 [00:00<00:00, 23.51it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelIDer3re6zp6hrme0ckb2rv79t7qcStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- an old rusted robot wearing pants and a jacket riding skis in a supermarket.
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T11:04:39.385191Z", "created_at": "2024-11-23T11:04:38.196000Z", "data_removed": false, "error": null, "id": "er3re6zp6hrme0ckb2rv79t7qc", "input": { "width": 1024, "height": 1024, "prompt": "an old rusted robot wearing pants and a jacket riding skis in a supermarket.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 61216\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.15it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.15it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.15it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.16it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.16it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.53it/s]", "metrics": { "predict_time": 1.181596895, "total_time": 1.189191 }, "output": "https://replicate.delivery/xezq/agKtJ2aLzUKpDRAb0xcLsXQsezrtZfU6m9jtubTJeFzOGtnnA/output.png", "started_at": "2024-11-23T11:04:38.203594Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-kmdeuihpbukelnj54xghhtc3xyq7ibr3afh74nfamaocniisubka", "get": "https://api.replicate.com/v1/predictions/er3re6zp6hrme0ckb2rv79t7qc", "cancel": "https://api.replicate.com/v1/predictions/er3re6zp6hrme0ckb2rv79t7qc/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 61216 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.15it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.15it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.15it/s] 71%|███████ | 12/17 [00:00<00:00, 22.16it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.16it/s] 100%|██████████| 17/17 [00:00<00:00, 23.53it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelIDdjdhxx98xsrma0ckb2s80r193mStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- professional portrait photo of an anthropomorphic cat wearing fancy gentleman hat and jacket walking in autumn forest.
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "professional portrait photo of an anthropomorphic cat wearing fancy gentleman hat and jacket walking in autumn forest.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "professional portrait photo of an anthropomorphic cat wearing fancy gentleman hat and jacket walking in autumn forest.", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "professional portrait photo of an anthropomorphic cat wearing fancy gentleman hat and jacket walking in autumn forest.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "professional portrait photo of an anthropomorphic cat wearing fancy gentleman hat and jacket walking in autumn forest.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T11:04:52.412067Z", "created_at": "2024-11-23T11:04:51.182000Z", "data_removed": false, "error": null, "id": "djdhxx98xsrma0ckb2s80r193m", "input": { "width": 1024, "height": 1024, "prompt": "professional portrait photo of an anthropomorphic cat wearing fancy gentleman hat and jacket walking in autumn forest.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 58382\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.15it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.14it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.15it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.14it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.15it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.53it/s]", "metrics": { "predict_time": 1.223651544, "total_time": 1.230067 }, "output": "https://replicate.delivery/xezq/g2J3cSjBsi7eParE3BcAxHR4XzBDczaBlCn128Dgt4VqR75JA/output.png", "started_at": "2024-11-23T11:04:51.188416Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-l23soo67ukmbxqokxiaqhayhtacqmbqo6z5c7xdrzihhije4lh7a", "get": "https://api.replicate.com/v1/predictions/djdhxx98xsrma0ckb2s80r193m", "cancel": "https://api.replicate.com/v1/predictions/djdhxx98xsrma0ckb2s80r193m/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 58382 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.15it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.14it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.15it/s] 71%|███████ | 12/17 [00:00<00:00, 22.14it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.15it/s] 100%|██████████| 17/17 [00:00<00:00, 23.53it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelIDrndnxgpqfsrm80ckb2s99xcejgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- Astronaut in a jungle, cold color palette, muted colors, detailed
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "Astronaut in a jungle, cold color palette, muted colors, detailed", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "Astronaut in a jungle, cold color palette, muted colors, detailed", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "Astronaut in a jungle, cold color palette, muted colors, detailed", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "Astronaut in a jungle, cold color palette, muted colors, detailed", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T11:05:37.017594Z", "created_at": "2024-11-23T11:05:35.870000Z", "data_removed": false, "error": null, "id": "rndnxgpqfsrm80ckb2s99xcejg", "input": { "width": 1024, "height": 1024, "prompt": "Astronaut in a jungle, cold color palette, muted colors, detailed", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 61039\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 21.99it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.06it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.07it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.09it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.10it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.46it/s]", "metrics": { "predict_time": 1.141343185, "total_time": 1.147594 }, "output": "https://replicate.delivery/xezq/UdVbPhKQrWJVG1lRjD4GgP9EIpujzfZXp2sweCsBaRDBk2zTA/output.png", "started_at": "2024-11-23T11:05:35.876251Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-tsickwqgfk6vtpdyckstdjme2lsbwfmx5qyvc5taldqjqu7p55xq", "get": "https://api.replicate.com/v1/predictions/rndnxgpqfsrm80ckb2s99xcejg", "cancel": "https://api.replicate.com/v1/predictions/rndnxgpqfsrm80ckb2s99xcejg/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 61039 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 21.99it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.06it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.07it/s] 71%|███████ | 12/17 [00:00<00:00, 22.09it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.10it/s] 100%|██████████| 17/17 [00:00<00:00, 23.46it/s]
Prediction
nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1ModelIDfk3hcfcrvsrm80ckb2svqqztbmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- A very detailed and realistic full body photo set of a tall, slim, and athletic Shiba Inu in a white oversized straight t-shirt, white shorts, and short white shoes.
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "A very detailed and realistic full body photo set of a tall, slim, and athletic Shiba Inu in a white oversized straight t-shirt, white shorts, and short white shoes.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", { input: { width: 1024, height: 1024, prompt: "A very detailed and realistic full body photo set of a tall, slim, and athletic Shiba Inu in a white oversized straight t-shirt, white shorts, and short white shoes.", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", input={ "width": 1024, "height": 1024, "prompt": "A very detailed and realistic full body photo set of a tall, slim, and athletic Shiba Inu in a white oversized straight t-shirt, white shorts, and short white shoes.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1", "input": { "width": 1024, "height": 1024, "prompt": "A very detailed and realistic full body photo set of a tall, slim, and athletic Shiba Inu in a white oversized straight t-shirt, white shorts, and short white shoes.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-23T11:06:26.403338Z", "created_at": "2024-11-23T11:06:25.374000Z", "data_removed": false, "error": null, "id": "fk3hcfcrvsrm80ckb2svqqztbm", "input": { "width": 1024, "height": 1024, "prompt": "A very detailed and realistic full body photo set of a tall, slim, and athletic Shiba Inu in a white oversized straight t-shirt, white shorts, and short white shoes.", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 16505\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.12it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.11it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.12it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.14it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.14it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.51it/s]", "metrics": { "predict_time": 1.019317268, "total_time": 1.029338 }, "output": "https://replicate.delivery/xezq/S0rfkwInC5RFEylRjOdDFeDAVLrOCRLSOZMpa2CczhNyk2zTA/output.png", "started_at": "2024-11-23T11:06:25.384020Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-jhhzh2kjw3ndtn7ocgz5lfts4fd73seorsbceyrebmmd5stuwi4a", "get": "https://api.replicate.com/v1/predictions/fk3hcfcrvsrm80ckb2svqqztbm", "cancel": "https://api.replicate.com/v1/predictions/fk3hcfcrvsrm80ckb2svqqztbm/cancel" }, "version": "0c65d5fd6b12e7c6f083e1f24c900eadfd0cb636a98ab6fa7a461337c256c1c1" }
Generated inUsing seed: 16505 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.12it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.11it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.12it/s] 71%|███████ | 12/17 [00:00<00:00, 22.14it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.14it/s] 100%|██████████| 17/17 [00:00<00:00, 23.51it/s]
Prediction
nvidia/sana:88312dcb9eaa543d7f8721e092053e8bb901a45a5d3c63c84e0a5aa7c247df33ModelIDzj27sz9f0xrma0ckbf0v455ypmStatusSucceededSourceWebHardwareH100Total durationCreatedby @chenxwhInput
- width
- 1024
- height
- 1024
- prompt
- a cyberpunk cat with a neon sign that says "Sana"
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 1024, "height": 1024, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:88312dcb9eaa543d7f8721e092053e8bb901a45a5d3c63c84e0a5aa7c247df33", { input: { width: 1024, height: 1024, prompt: "a cyberpunk cat with a neon sign that says \"Sana\"", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:88312dcb9eaa543d7f8721e092053e8bb901a45a5d3c63c84e0a5aa7c247df33", input={ "width": 1024, "height": 1024, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "88312dcb9eaa543d7f8721e092053e8bb901a45a5d3c63c84e0a5aa7c247df33", "input": { "width": 1024, "height": 1024, "prompt": "a cyberpunk cat with a neon sign that says \\"Sana\\"", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-24T01:20:08.636722Z", "created_at": "2024-11-24T01:20:07.431000Z", "data_removed": false, "error": null, "id": "zj27sz9f0xrma0ckbf0v455ypm", "input": { "width": 1024, "height": 1024, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 49609\n 0%| | 0/17 [00:00<?, ?it/s]\n 18%|█▊ | 3/17 [00:00<00:00, 22.20it/s]\n 35%|███▌ | 6/17 [00:00<00:00, 22.18it/s]\n 53%|█████▎ | 9/17 [00:00<00:00, 22.17it/s]\n 71%|███████ | 12/17 [00:00<00:00, 22.17it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 22.17it/s]\n100%|██████████| 17/17 [00:00<00:00, 23.56it/s]", "metrics": { "predict_time": 1.198414056, "total_time": 1.205722 }, "output": "https://replicate.delivery/xezq/SRGSBB0ygzb3JVkLCW2A0Kofze4aD1KqHa2KOoW9oeejUMQPB/output.png", "started_at": "2024-11-24T01:20:07.438308Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-vdagiyuf62kw5uzmjpckui5yvzja7tso6ttlqcec7mb6qhghxpfa", "get": "https://api.replicate.com/v1/predictions/zj27sz9f0xrma0ckbf0v455ypm", "cancel": "https://api.replicate.com/v1/predictions/zj27sz9f0xrma0ckbf0v455ypm/cancel" }, "version": "88312dcb9eaa543d7f8721e092053e8bb901a45a5d3c63c84e0a5aa7c247df33" }
Generated inUsing seed: 49609 0%| | 0/17 [00:00<?, ?it/s] 18%|█▊ | 3/17 [00:00<00:00, 22.20it/s] 35%|███▌ | 6/17 [00:00<00:00, 22.18it/s] 53%|█████▎ | 9/17 [00:00<00:00, 22.17it/s] 71%|███████ | 12/17 [00:00<00:00, 22.17it/s] 88%|████████▊ | 15/17 [00:00<00:00, 22.17it/s] 100%|██████████| 17/17 [00:00<00:00, 23.56it/s]
Prediction
nvidia/sana:c6b5d2b7459910fec94432e9e1203c3cdce92d6db20f714f1355747990b52fa6ModelID3jw9haezy5rmc0ckkkhb3ewp9mStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- width
- 512
- height
- 512
- prompt
- a cyberpunk cat with a neon sign that says "Sana"
- model_variant
- 600M-512px-multilang
- guidance_scale
- 5
- negative_prompt
- pag_guidance_scale
- 2
- num_inference_steps
- 18
{ "width": 512, "height": 512, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "model_variant": "600M-512px-multilang", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }
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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nvidia/sana:c6b5d2b7459910fec94432e9e1203c3cdce92d6db20f714f1355747990b52fa6", { input: { width: 512, height: 512, prompt: "a cyberpunk cat with a neon sign that says \"Sana\"", model_variant: "600M-512px-multilang", guidance_scale: 5, negative_prompt: "", pag_guidance_scale: 2, num_inference_steps: 18 } } ); // 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 nvidia/sana using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nvidia/sana:c6b5d2b7459910fec94432e9e1203c3cdce92d6db20f714f1355747990b52fa6", input={ "width": 512, "height": 512, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "model_variant": "600M-512px-multilang", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run nvidia/sana 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": "c6b5d2b7459910fec94432e9e1203c3cdce92d6db20f714f1355747990b52fa6", "input": { "width": 512, "height": 512, "prompt": "a cyberpunk cat with a neon sign that says \\"Sana\\"", "model_variant": "600M-512px-multilang", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-06T16:52:15.007250Z", "created_at": "2024-12-06T16:52:14.449000Z", "data_removed": false, "error": null, "id": "3jw9haezy5rmc0ckkkhb3ewp9m", "input": { "width": 512, "height": 512, "prompt": "a cyberpunk cat with a neon sign that says \"Sana\"", "model_variant": "600M-512px-multilang", "guidance_scale": 5, "negative_prompt": "", "pag_guidance_scale": 2, "num_inference_steps": 18 }, "logs": "Using seed: 1628\n 0%| | 0/17 [00:00<?, ?it/s]\n 29%|██▉ | 5/17 [00:00<00:00, 43.08it/s]\n 59%|█████▉ | 10/17 [00:00<00:00, 43.35it/s]\n 88%|████████▊ | 15/17 [00:00<00:00, 43.61it/s]\n100%|██████████| 17/17 [00:00<00:00, 46.21it/s]", "metrics": { "predict_time": 0.55227876, "total_time": 0.55825 }, "output": "https://replicate.delivery/xezq/hl2BiJtO2yYVF5bFfPxRHlyD2aJPJSSPwkdCbTWmJKlf2N4TA/output.png", "started_at": "2024-12-06T16:52:14.454971Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-raxaxqckvhburdr2kpb3n33x7slhdqsdisjw5uizqjg7y5nbi7fa", "get": "https://api.replicate.com/v1/predictions/3jw9haezy5rmc0ckkkhb3ewp9m", "cancel": "https://api.replicate.com/v1/predictions/3jw9haezy5rmc0ckkkhb3ewp9m/cancel" }, "version": "c6b5d2b7459910fec94432e9e1203c3cdce92d6db20f714f1355747990b52fa6" }
Generated inUsing seed: 1628 0%| | 0/17 [00:00<?, ?it/s] 29%|██▉ | 5/17 [00:00<00:00, 43.08it/s] 59%|█████▉ | 10/17 [00:00<00:00, 43.35it/s] 88%|████████▊ | 15/17 [00:00<00:00, 43.61it/s] 100%|██████████| 17/17 [00:00<00:00, 46.21it/s]
Want to make some of these yourself?
Run this model