stability-ai
/
stable-diffusion-3.5-large
A text-to-image model that generates high-resolution images with fine details. It supports various artistic styles and produces diverse outputs from the same prompt, thanks to Query-Key Normalization.
Prediction
stability-ai/stable-diffusion-3.5-largeOfficial modelIDw3xvn77rqsrm60cjphmryczjzgStatusSucceededSourceWebTotal durationCreatedInput
- cfg
- 3.5
- steps
- 28
- prompt
- Photo of three potions: the first potion is blue with the label “MANA”, the second potion is red with the label “HEALTH”, the third potion is green with the label “POISON”. Old apothecary
- aspect_ratio
- 1:1
- output_format
- webp
- output_quality
- 90
{ "cfg": 3.5, "steps": 28, "prompt": "Photo of three potions: the first potion is blue with the label “MANA”, the second potion is red with the label “HEALTH”, the third potion is green with the label “POISON”. Old apothecary", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { cfg: 3.5, steps: 28, prompt: "Photo of three potions: the first potion is blue with the label “MANA”, the second potion is red with the label “HEALTH”, the third potion is green with the label “POISON”. Old apothecary", aspect_ratio: "1:1", output_format: "webp", output_quality: 90 }; const output = await replicate.run("stability-ai/stable-diffusion-3.5-large", { input }); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "stability-ai/stable-diffusion-3.5-large", input={ "cfg": 3.5, "steps": 28, "prompt": "Photo of three potions: the first potion is blue with the label “MANA”, the second potion is red with the label “HEALTH”, the third potion is green with the label “POISON”. Old apothecary", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run stability-ai/stable-diffusion-3.5-large 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 $'{ "input": { "cfg": 3.5, "steps": 28, "prompt": "Photo of three potions: the first potion is blue with the label “MANA”, the second potion is red with the label “HEALTH”, the third potion is green with the label “POISON”. Old apothecary", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } }' \ https://api.replicate.com/v1/models/stability-ai/stable-diffusion-3.5-large/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-22T13:28:23.168062Z", "created_at": "2024-10-22T13:28:16.830000Z", "data_removed": false, "error": null, "id": "w3xvn77rqsrm60cjphmryczjzg", "input": { "cfg": 3.5, "steps": 28, "prompt": "Photo of three potions: the first potion is blue with the label “MANA”, the second potion is red with the label “HEALTH”, the third potion is green with the label “POISON”. Old apothecary", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }, "logs": "Random seed set to: 1865532289\nRunning workflow\ngot prompt\nExecuting node 294, title: KSampler, class type: KSampler\n0%| | 0/28 [00:00<?, ?it/s]\n4%|▎ | 1/28 [00:00<00:03, 7.48it/s]\n7%|▋ | 2/28 [00:00<00:05, 4.60it/s]\n11%|█ | 3/28 [00:00<00:05, 4.73it/s]\n14%|█▍ | 4/28 [00:00<00:05, 4.78it/s]\n18%|█▊ | 5/28 [00:01<00:04, 4.81it/s]\n21%|██▏ | 6/28 [00:01<00:04, 4.84it/s]\n25%|██▌ | 7/28 [00:01<00:04, 4.85it/s]\n29%|██▊ | 8/28 [00:01<00:04, 4.86it/s]\n32%|███▏ | 9/28 [00:01<00:03, 4.86it/s]\n36%|███▌ | 10/28 [00:02<00:03, 4.87it/s]\n39%|███▉ | 11/28 [00:02<00:03, 4.87it/s]\n43%|████▎ | 12/28 [00:02<00:03, 4.87it/s]\n46%|████▋ | 13/28 [00:02<00:03, 4.88it/s]\n50%|█████ | 14/28 [00:02<00:02, 4.88it/s]\n54%|█████▎ | 15/28 [00:03<00:02, 4.88it/s]\n57%|█████▋ | 16/28 [00:03<00:02, 4.88it/s]\n61%|██████ | 17/28 [00:03<00:02, 4.88it/s]\n64%|██████▍ | 18/28 [00:03<00:02, 4.88it/s]\n68%|██████▊ | 19/28 [00:03<00:01, 4.88it/s]\n71%|███████▏ | 20/28 [00:04<00:01, 4.88it/s]\n75%|███████▌ | 21/28 [00:04<00:01, 4.80it/s]\n79%|███████▊ | 22/28 [00:04<00:01, 4.82it/s]\n82%|████████▏ | 23/28 [00:04<00:01, 4.84it/s]\n86%|████████▌ | 24/28 [00:04<00:00, 4.84it/s]\n89%|████████▉ | 25/28 [00:05<00:00, 4.85it/s]\n93%|█████████▎| 26/28 [00:05<00:00, 4.86it/s]\n96%|█████████▋| 27/28 [00:05<00:00, 4.86it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.86it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.87it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 309, title: Save Image, class type: SaveImage\nPrompt executed in 6.06 seconds\noutputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8_sd3.5L_00001_.png", "metrics": { "image_count": 1, "predict_time": 6.331162777, "total_time": 6.338062 }, "output": [ "https://replicate.delivery/yhqm/6ctUeWKkzZXxTy1CHx7R94ysbwB4nrpiyM3pLVvODsq70q0JA/R8_sd3.5L_00001_.webp" ], "started_at": "2024-10-22T13:28:16.836899Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/w3xvn77rqsrm60cjphmryczjzg", "cancel": "https://api.replicate.com/v1/predictions/w3xvn77rqsrm60cjphmryczjzg/cancel" }, "version": "hidden" }Generated inRandom seed set to: 1865532289 Running workflow got prompt Executing node 294, title: KSampler, class type: KSampler 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:03, 7.48it/s] 7%|▋ | 2/28 [00:00<00:05, 4.60it/s] 11%|█ | 3/28 [00:00<00:05, 4.73it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.78it/s] 18%|█▊ | 5/28 [00:01<00:04, 4.81it/s] 21%|██▏ | 6/28 [00:01<00:04, 4.84it/s] 25%|██▌ | 7/28 [00:01<00:04, 4.85it/s] 29%|██▊ | 8/28 [00:01<00:04, 4.86it/s] 32%|███▏ | 9/28 [00:01<00:03, 4.86it/s] 36%|███▌ | 10/28 [00:02<00:03, 4.87it/s] 39%|███▉ | 11/28 [00:02<00:03, 4.87it/s] 43%|████▎ | 12/28 [00:02<00:03, 4.87it/s] 46%|████▋ | 13/28 [00:02<00:03, 4.88it/s] 50%|█████ | 14/28 [00:02<00:02, 4.88it/s] 54%|█████▎ | 15/28 [00:03<00:02, 4.88it/s] 57%|█████▋ | 16/28 [00:03<00:02, 4.88it/s] 61%|██████ | 17/28 [00:03<00:02, 4.88it/s] 64%|██████▍ | 18/28 [00:03<00:02, 4.88it/s] 68%|██████▊ | 19/28 [00:03<00:01, 4.88it/s] 71%|███████▏ | 20/28 [00:04<00:01, 4.88it/s] 75%|███████▌ | 21/28 [00:04<00:01, 4.80it/s] 79%|███████▊ | 22/28 [00:04<00:01, 4.82it/s] 82%|████████▏ | 23/28 [00:04<00:01, 4.84it/s] 86%|████████▌ | 24/28 [00:04<00:00, 4.84it/s] 89%|████████▉ | 25/28 [00:05<00:00, 4.85it/s] 93%|█████████▎| 26/28 [00:05<00:00, 4.86it/s] 96%|█████████▋| 27/28 [00:05<00:00, 4.86it/s] 100%|██████████| 28/28 [00:05<00:00, 4.86it/s] 100%|██████████| 28/28 [00:05<00:00, 4.87it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 309, title: Save Image, class type: SaveImage Prompt executed in 6.06 seconds outputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== R8_sd3.5L_00001_.pngPrediction
stability-ai/stable-diffusion-3.5-largeOfficial modelID2fzx24pt6srm60cjphnv6214a0StatusSucceededSourceWebTotal durationCreatedInput
- cfg
- 3.5
- steps
- 28
- prompt
- Scene of a giant ancient tortoise with a fantasy city built on its back. The tortoise’s shell is covered in lush, dense forest with towering trees and a hidden, misty village nestled in the foliage. The city consists of intricately designed buildings that blend seamlessly with the natural environment, featuring rope bridges connecting different sections of the city
- aspect_ratio
- 1:1
- output_format
- webp
- output_quality
- 90
{ "cfg": 3.5, "steps": 28, "prompt": "Scene of a giant ancient tortoise with a fantasy city built on its back. The tortoise’s shell is covered in lush, dense forest with towering trees and a hidden, misty village nestled in the foliage. The city consists of intricately designed buildings that blend seamlessly with the natural environment, featuring rope bridges connecting different sections of the city", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { cfg: 3.5, steps: 28, prompt: "Scene of a giant ancient tortoise with a fantasy city built on its back. The tortoise’s shell is covered in lush, dense forest with towering trees and a hidden, misty village nestled in the foliage. The city consists of intricately designed buildings that blend seamlessly with the natural environment, featuring rope bridges connecting different sections of the city", aspect_ratio: "1:1", output_format: "webp", output_quality: 90 }; const output = await replicate.run("stability-ai/stable-diffusion-3.5-large", { input }); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "stability-ai/stable-diffusion-3.5-large", input={ "cfg": 3.5, "steps": 28, "prompt": "Scene of a giant ancient tortoise with a fantasy city built on its back. The tortoise’s shell is covered in lush, dense forest with towering trees and a hidden, misty village nestled in the foliage. The city consists of intricately designed buildings that blend seamlessly with the natural environment, featuring rope bridges connecting different sections of the city", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run stability-ai/stable-diffusion-3.5-large 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 $'{ "input": { "cfg": 3.5, "steps": 28, "prompt": "Scene of a giant ancient tortoise with a fantasy city built on its back. The tortoise’s shell is covered in lush, dense forest with towering trees and a hidden, misty village nestled in the foliage. The city consists of intricately designed buildings that blend seamlessly with the natural environment, featuring rope bridges connecting different sections of the city", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } }' \ https://api.replicate.com/v1/models/stability-ai/stable-diffusion-3.5-large/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-22T13:30:26.431626Z", "created_at": "2024-10-22T13:30:20.086000Z", "data_removed": false, "error": null, "id": "2fzx24pt6srm60cjphnv6214a0", "input": { "cfg": 3.5, "steps": 28, "prompt": "Scene of a giant ancient tortoise with a fantasy city built on its back. The tortoise’s shell is covered in lush, dense forest with towering trees and a hidden, misty village nestled in the foliage. The city consists of intricately designed buildings that blend seamlessly with the natural environment, featuring rope bridges connecting different sections of the city", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }, "logs": "Random seed set to: 2133937269\nRunning workflow\ngot prompt\nExecuting node 294, title: KSampler, class type: KSampler\n0%| | 0/28 [00:00<?, ?it/s]\n4%|▎ | 1/28 [00:00<00:04, 5.50it/s]\n7%|▋ | 2/28 [00:00<00:05, 4.40it/s]\n11%|█ | 3/28 [00:00<00:05, 4.45it/s]\n14%|█▍ | 4/28 [00:00<00:05, 4.48it/s]\n18%|█▊ | 5/28 [00:01<00:05, 4.50it/s]\n21%|██▏ | 6/28 [00:01<00:04, 4.51it/s]\n25%|██▌ | 7/28 [00:01<00:04, 4.52it/s]\n29%|██▊ | 8/28 [00:01<00:04, 4.52it/s]\n32%|███▏ | 9/28 [00:01<00:04, 4.63it/s]\n36%|███▌ | 10/28 [00:02<00:03, 4.70it/s]\n39%|███▉ | 11/28 [00:02<00:03, 4.75it/s]\n43%|████▎ | 12/28 [00:02<00:03, 4.79it/s]\n46%|████▋ | 13/28 [00:02<00:03, 4.81it/s]\n50%|█████ | 14/28 [00:02<00:02, 4.83it/s]\n54%|█████▎ | 15/28 [00:03<00:02, 4.84it/s]\n57%|█████▋ | 16/28 [00:03<00:02, 4.85it/s]\n61%|██████ | 17/28 [00:03<00:02, 4.86it/s]\n64%|██████▍ | 18/28 [00:03<00:02, 4.86it/s]\n68%|██████▊ | 19/28 [00:04<00:01, 4.86it/s]\n71%|███████▏ | 20/28 [00:04<00:01, 4.87it/s]\n75%|███████▌ | 21/28 [00:04<00:01, 4.87it/s]\n79%|███████▊ | 22/28 [00:04<00:01, 4.87it/s]\n82%|████████▏ | 23/28 [00:04<00:01, 4.87it/s]\n86%|████████▌ | 24/28 [00:05<00:00, 4.87it/s]\n89%|████████▉ | 25/28 [00:05<00:00, 4.87it/s]\n93%|█████████▎| 26/28 [00:05<00:00, 4.87it/s]\n96%|█████████▋| 27/28 [00:05<00:00, 4.86it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.86it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.77it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 309, title: Save Image, class type: SaveImage\nPrompt executed in 6.17 seconds\noutputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8_sd3.5L_00001_.png", "metrics": { "image_count": 1, "predict_time": 6.337574761, "total_time": 6.345626 }, "output": [ "https://replicate.delivery/yhqm/QJWJKJxtF6aSAljJuAF6t1Qbf2hmxkPtKzNzd36xPGR51q0JA/R8_sd3.5L_00001_.webp" ], "started_at": "2024-10-22T13:30:20.094051Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/2fzx24pt6srm60cjphnv6214a0", "cancel": "https://api.replicate.com/v1/predictions/2fzx24pt6srm60cjphnv6214a0/cancel" }, "version": "hidden" }Generated inRandom seed set to: 2133937269 Running workflow got prompt Executing node 294, title: KSampler, class type: KSampler 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:04, 5.50it/s] 7%|▋ | 2/28 [00:00<00:05, 4.40it/s] 11%|█ | 3/28 [00:00<00:05, 4.45it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.48it/s] 18%|█▊ | 5/28 [00:01<00:05, 4.50it/s] 21%|██▏ | 6/28 [00:01<00:04, 4.51it/s] 25%|██▌ | 7/28 [00:01<00:04, 4.52it/s] 29%|██▊ | 8/28 [00:01<00:04, 4.52it/s] 32%|███▏ | 9/28 [00:01<00:04, 4.63it/s] 36%|███▌ | 10/28 [00:02<00:03, 4.70it/s] 39%|███▉ | 11/28 [00:02<00:03, 4.75it/s] 43%|████▎ | 12/28 [00:02<00:03, 4.79it/s] 46%|████▋ | 13/28 [00:02<00:03, 4.81it/s] 50%|█████ | 14/28 [00:02<00:02, 4.83it/s] 54%|█████▎ | 15/28 [00:03<00:02, 4.84it/s] 57%|█████▋ | 16/28 [00:03<00:02, 4.85it/s] 61%|██████ | 17/28 [00:03<00:02, 4.86it/s] 64%|██████▍ | 18/28 [00:03<00:02, 4.86it/s] 68%|██████▊ | 19/28 [00:04<00:01, 4.86it/s] 71%|███████▏ | 20/28 [00:04<00:01, 4.87it/s] 75%|███████▌ | 21/28 [00:04<00:01, 4.87it/s] 79%|███████▊ | 22/28 [00:04<00:01, 4.87it/s] 82%|████████▏ | 23/28 [00:04<00:01, 4.87it/s] 86%|████████▌ | 24/28 [00:05<00:00, 4.87it/s] 89%|████████▉ | 25/28 [00:05<00:00, 4.87it/s] 93%|█████████▎| 26/28 [00:05<00:00, 4.87it/s] 96%|█████████▋| 27/28 [00:05<00:00, 4.86it/s] 100%|██████████| 28/28 [00:05<00:00, 4.86it/s] 100%|██████████| 28/28 [00:05<00:00, 4.77it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 309, title: Save Image, class type: SaveImage Prompt executed in 6.17 seconds outputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== R8_sd3.5L_00001_.pngPrediction
stability-ai/stable-diffusion-3.5-largeOfficial modelIDjryp9p71mxrm00cjphpt6aact8StatusSucceededSourceWebTotal durationCreatedInput
- cfg
- 3.5
- steps
- 28
- prompt
- collage art ‘We’re Leaving For the Future’ 1980s #vaporwave aesthetic internet art glued layered magazine cutout image shape scrap, torn ragged paper art, BASIC code, halftone, #pixelart
- aspect_ratio
- 1:1
- output_format
- webp
- output_quality
- 90
{ "cfg": 3.5, "steps": 28, "prompt": "collage art ‘We’re Leaving For the Future’ 1980s #vaporwave aesthetic internet art glued layered magazine cutout image shape scrap, torn ragged paper art, BASIC code, halftone, #pixelart ", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { cfg: 3.5, steps: 28, prompt: "collage art ‘We’re Leaving For the Future’ 1980s #vaporwave aesthetic internet art glued layered magazine cutout image shape scrap, torn ragged paper art, BASIC code, halftone, #pixelart ", aspect_ratio: "1:1", output_format: "webp", output_quality: 90 }; const output = await replicate.run("stability-ai/stable-diffusion-3.5-large", { input }); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "stability-ai/stable-diffusion-3.5-large", input={ "cfg": 3.5, "steps": 28, "prompt": "collage art ‘We’re Leaving For the Future’ 1980s #vaporwave aesthetic internet art glued layered magazine cutout image shape scrap, torn ragged paper art, BASIC code, halftone, #pixelart ", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run stability-ai/stable-diffusion-3.5-large 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 $'{ "input": { "cfg": 3.5, "steps": 28, "prompt": "collage art ‘We’re Leaving For the Future’ 1980s #vaporwave aesthetic internet art glued layered magazine cutout image shape scrap, torn ragged paper art, BASIC code, halftone, #pixelart ", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } }' \ https://api.replicate.com/v1/models/stability-ai/stable-diffusion-3.5-large/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-22T13:32:39.293178Z", "created_at": "2024-10-22T13:32:33.063000Z", "data_removed": false, "error": null, "id": "jryp9p71mxrm00cjphpt6aact8", "input": { "cfg": 3.5, "steps": 28, "prompt": "collage art ‘We’re Leaving For the Future’ 1980s #vaporwave aesthetic internet art glued layered magazine cutout image shape scrap, torn ragged paper art, BASIC code, halftone, #pixelart ", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }, "logs": "Random seed set to: 1941557087\nRunning workflow\ngot prompt\nExecuting node 294, title: KSampler, class type: KSampler\n0%| | 0/28 [00:00<?, ?it/s]\n4%|▎ | 1/28 [00:00<00:03, 7.41it/s]\n7%|▋ | 2/28 [00:00<00:05, 4.60it/s]\n11%|█ | 3/28 [00:00<00:05, 4.72it/s]\n14%|█▍ | 4/28 [00:00<00:05, 4.77it/s]\n18%|█▊ | 5/28 [00:01<00:04, 4.81it/s]\n21%|██▏ | 6/28 [00:01<00:04, 4.83it/s]\n25%|██▌ | 7/28 [00:01<00:04, 4.84it/s]\n29%|██▊ | 8/28 [00:01<00:04, 4.85it/s]\n32%|███▏ | 9/28 [00:01<00:03, 4.85it/s]\n36%|███▌ | 10/28 [00:02<00:03, 4.85it/s]\n39%|███▉ | 11/28 [00:02<00:03, 4.85it/s]\n43%|████▎ | 12/28 [00:02<00:03, 4.86it/s]\n46%|████▋ | 13/28 [00:02<00:03, 4.86it/s]\n50%|█████ | 14/28 [00:02<00:02, 4.86it/s]\n54%|█████▎ | 15/28 [00:03<00:02, 4.86it/s]\n57%|█████▋ | 16/28 [00:03<00:02, 4.87it/s]\n61%|██████ | 17/28 [00:03<00:02, 4.86it/s]\n64%|██████▍ | 18/28 [00:03<00:02, 4.87it/s]\n68%|██████▊ | 19/28 [00:03<00:01, 4.87it/s]\n71%|███████▏ | 20/28 [00:04<00:01, 4.87it/s]\n75%|███████▌ | 21/28 [00:04<00:01, 4.87it/s]\n79%|███████▊ | 22/28 [00:04<00:01, 4.87it/s]\n82%|████████▏ | 23/28 [00:04<00:01, 4.86it/s]\n86%|████████▌ | 24/28 [00:04<00:00, 4.86it/s]\n89%|████████▉ | 25/28 [00:05<00:00, 4.86it/s]\n93%|█████████▎| 26/28 [00:05<00:00, 4.86it/s]\n96%|█████████▋| 27/28 [00:05<00:00, 4.86it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.86it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.87it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 309, title: Save Image, class type: SaveImage\nPrompt executed in 6.05 seconds\noutputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8_sd3.5L_00001_.png", "metrics": { "image_count": 1, "predict_time": 6.222313639, "total_time": 6.230178 }, "output": [ "https://replicate.delivery/yhqm/mxMdiQ52lxLCGBbuyW6YHpg1k47JVXuRgEOeTFgfAYfubrSnA/R8_sd3.5L_00001_.webp" ], "started_at": "2024-10-22T13:32:33.070864Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jryp9p71mxrm00cjphpt6aact8", "cancel": "https://api.replicate.com/v1/predictions/jryp9p71mxrm00cjphpt6aact8/cancel" }, "version": "hidden" }Generated inRandom seed set to: 1941557087 Running workflow got prompt Executing node 294, title: KSampler, class type: KSampler 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:03, 7.41it/s] 7%|▋ | 2/28 [00:00<00:05, 4.60it/s] 11%|█ | 3/28 [00:00<00:05, 4.72it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.77it/s] 18%|█▊ | 5/28 [00:01<00:04, 4.81it/s] 21%|██▏ | 6/28 [00:01<00:04, 4.83it/s] 25%|██▌ | 7/28 [00:01<00:04, 4.84it/s] 29%|██▊ | 8/28 [00:01<00:04, 4.85it/s] 32%|███▏ | 9/28 [00:01<00:03, 4.85it/s] 36%|███▌ | 10/28 [00:02<00:03, 4.85it/s] 39%|███▉ | 11/28 [00:02<00:03, 4.85it/s] 43%|████▎ | 12/28 [00:02<00:03, 4.86it/s] 46%|████▋ | 13/28 [00:02<00:03, 4.86it/s] 50%|█████ | 14/28 [00:02<00:02, 4.86it/s] 54%|█████▎ | 15/28 [00:03<00:02, 4.86it/s] 57%|█████▋ | 16/28 [00:03<00:02, 4.87it/s] 61%|██████ | 17/28 [00:03<00:02, 4.86it/s] 64%|██████▍ | 18/28 [00:03<00:02, 4.87it/s] 68%|██████▊ | 19/28 [00:03<00:01, 4.87it/s] 71%|███████▏ | 20/28 [00:04<00:01, 4.87it/s] 75%|███████▌ | 21/28 [00:04<00:01, 4.87it/s] 79%|███████▊ | 22/28 [00:04<00:01, 4.87it/s] 82%|████████▏ | 23/28 [00:04<00:01, 4.86it/s] 86%|████████▌ | 24/28 [00:04<00:00, 4.86it/s] 89%|████████▉ | 25/28 [00:05<00:00, 4.86it/s] 93%|█████████▎| 26/28 [00:05<00:00, 4.86it/s] 96%|█████████▋| 27/28 [00:05<00:00, 4.86it/s] 100%|██████████| 28/28 [00:05<00:00, 4.86it/s] 100%|██████████| 28/28 [00:05<00:00, 4.87it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 309, title: Save Image, class type: SaveImage Prompt executed in 6.05 seconds outputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== R8_sd3.5L_00001_.pngPrediction
stability-ai/stable-diffusion-3.5-largeOfficial modelIDtnp1d64155rm20cjphwsj994h4StatusSucceededSourceWebTotal durationCreatedInput
- cfg
- 3.5
- steps
- 28
- prompt
- a captivating anime-style illustration of a young woman in a white astronaut suit. She has long, dark wavy hair. Surrounding the astronaut are vibrant orange flowers with yellow centers. The background itself is a mesmerizing night sky filled with countless stars
- aspect_ratio
- 1:1
- output_format
- webp
- output_quality
- 90
{ "cfg": 3.5, "steps": 28, "prompt": "a captivating anime-style illustration of a young woman in a white astronaut suit. She has long, dark wavy hair. Surrounding the astronaut are vibrant orange flowers with yellow centers. The background itself is a mesmerizing night sky filled with countless stars", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { cfg: 3.5, steps: 28, prompt: "a captivating anime-style illustration of a young woman in a white astronaut suit. She has long, dark wavy hair. Surrounding the astronaut are vibrant orange flowers with yellow centers. The background itself is a mesmerizing night sky filled with countless stars", aspect_ratio: "1:1", output_format: "webp", output_quality: 90 }; const output = await replicate.run("stability-ai/stable-diffusion-3.5-large", { input }); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "stability-ai/stable-diffusion-3.5-large", input={ "cfg": 3.5, "steps": 28, "prompt": "a captivating anime-style illustration of a young woman in a white astronaut suit. She has long, dark wavy hair. Surrounding the astronaut are vibrant orange flowers with yellow centers. The background itself is a mesmerizing night sky filled with countless stars", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run stability-ai/stable-diffusion-3.5-large 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 $'{ "input": { "cfg": 3.5, "steps": 28, "prompt": "a captivating anime-style illustration of a young woman in a white astronaut suit. She has long, dark wavy hair. Surrounding the astronaut are vibrant orange flowers with yellow centers. The background itself is a mesmerizing night sky filled with countless stars", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } }' \ https://api.replicate.com/v1/models/stability-ai/stable-diffusion-3.5-large/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-22T13:45:21.285794Z", "created_at": "2024-10-22T13:45:14.793000Z", "data_removed": false, "error": null, "id": "tnp1d64155rm20cjphwsj994h4", "input": { "cfg": 3.5, "steps": 28, "prompt": "a captivating anime-style illustration of a young woman in a white astronaut suit. She has long, dark wavy hair. Surrounding the astronaut are vibrant orange flowers with yellow centers. The background itself is a mesmerizing night sky filled with countless stars", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }, "logs": "Random seed set to: 3762959028\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 67, title: ConditioningZeroOut, class type: ConditioningZeroOut\nExecuting node 68, title: ConditioningSetTimestepRange, class type: ConditioningSetTimestepRange\nExecuting node 69, title: Conditioning (Combine), class type: ConditioningCombine\nExecuting node 294, title: KSampler, class type: KSampler\n0%| | 0/28 [00:00<?, ?it/s]\n4%|▎ | 1/28 [00:00<00:03, 7.51it/s]\n7%|▋ | 2/28 [00:00<00:05, 4.62it/s]\n11%|█ | 3/28 [00:00<00:05, 4.73it/s]\n14%|█▍ | 4/28 [00:00<00:05, 4.79it/s]\n18%|█▊ | 5/28 [00:01<00:04, 4.82it/s]\n21%|██▏ | 6/28 [00:01<00:04, 4.84it/s]\n25%|██▌ | 7/28 [00:01<00:04, 4.85it/s]\n29%|██▊ | 8/28 [00:01<00:04, 4.86it/s]\n32%|███▏ | 9/28 [00:01<00:03, 4.87it/s]\n36%|███▌ | 10/28 [00:02<00:03, 4.88it/s]\n39%|███▉ | 11/28 [00:02<00:03, 4.88it/s]\n43%|████▎ | 12/28 [00:02<00:03, 4.87it/s]\n46%|████▋ | 13/28 [00:02<00:03, 4.87it/s]\n50%|█████ | 14/28 [00:02<00:02, 4.87it/s]\n54%|█████▎ | 15/28 [00:03<00:02, 4.88it/s]\n57%|█████▋ | 16/28 [00:03<00:02, 4.88it/s]\n61%|██████ | 17/28 [00:03<00:02, 4.88it/s]\n64%|██████▍ | 18/28 [00:03<00:02, 4.88it/s]\n68%|██████▊ | 19/28 [00:03<00:01, 4.87it/s]\n71%|███████▏ | 20/28 [00:04<00:01, 4.87it/s]\n75%|███████▌ | 21/28 [00:04<00:01, 4.88it/s]\n79%|███████▊ | 22/28 [00:04<00:01, 4.88it/s]\n82%|████████▏ | 23/28 [00:04<00:01, 4.88it/s]\n86%|████████▌ | 24/28 [00:04<00:00, 4.88it/s]\n89%|████████▉ | 25/28 [00:05<00:00, 4.87it/s]\n93%|█████████▎| 26/28 [00:05<00:00, 4.88it/s]\n96%|█████████▋| 27/28 [00:05<00:00, 4.88it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.87it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.88it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 309, title: Save Image, class type: SaveImage\nPrompt executed in 6.13 seconds\noutputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8_sd3.5L_00001_.png", "metrics": { "image_count": 1, "predict_time": 6.484623575, "total_time": 6.492794 }, "output": [ "https://replicate.delivery/yhqm/PMawGj2JwA58MpmZKkCNE4adlQfMLRJ0wZG6VH5JtY648q0JA/R8_sd3.5L_00001_.webp" ], "started_at": "2024-10-22T13:45:14.801171Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tnp1d64155rm20cjphwsj994h4", "cancel": "https://api.replicate.com/v1/predictions/tnp1d64155rm20cjphwsj994h4/cancel" }, "version": "hidden" }Generated inRandom seed set to: 3762959028 Running workflow got prompt Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Executing node 67, title: ConditioningZeroOut, class type: ConditioningZeroOut Executing node 68, title: ConditioningSetTimestepRange, class type: ConditioningSetTimestepRange Executing node 69, title: Conditioning (Combine), class type: ConditioningCombine Executing node 294, title: KSampler, class type: KSampler 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:03, 7.51it/s] 7%|▋ | 2/28 [00:00<00:05, 4.62it/s] 11%|█ | 3/28 [00:00<00:05, 4.73it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.79it/s] 18%|█▊ | 5/28 [00:01<00:04, 4.82it/s] 21%|██▏ | 6/28 [00:01<00:04, 4.84it/s] 25%|██▌ | 7/28 [00:01<00:04, 4.85it/s] 29%|██▊ | 8/28 [00:01<00:04, 4.86it/s] 32%|███▏ | 9/28 [00:01<00:03, 4.87it/s] 36%|███▌ | 10/28 [00:02<00:03, 4.88it/s] 39%|███▉ | 11/28 [00:02<00:03, 4.88it/s] 43%|████▎ | 12/28 [00:02<00:03, 4.87it/s] 46%|████▋ | 13/28 [00:02<00:03, 4.87it/s] 50%|█████ | 14/28 [00:02<00:02, 4.87it/s] 54%|█████▎ | 15/28 [00:03<00:02, 4.88it/s] 57%|█████▋ | 16/28 [00:03<00:02, 4.88it/s] 61%|██████ | 17/28 [00:03<00:02, 4.88it/s] 64%|██████▍ | 18/28 [00:03<00:02, 4.88it/s] 68%|██████▊ | 19/28 [00:03<00:01, 4.87it/s] 71%|███████▏ | 20/28 [00:04<00:01, 4.87it/s] 75%|███████▌ | 21/28 [00:04<00:01, 4.88it/s] 79%|███████▊ | 22/28 [00:04<00:01, 4.88it/s] 82%|████████▏ | 23/28 [00:04<00:01, 4.88it/s] 86%|████████▌ | 24/28 [00:04<00:00, 4.88it/s] 89%|████████▉ | 25/28 [00:05<00:00, 4.87it/s] 93%|█████████▎| 26/28 [00:05<00:00, 4.88it/s] 96%|█████████▋| 27/28 [00:05<00:00, 4.88it/s] 100%|██████████| 28/28 [00:05<00:00, 4.87it/s] 100%|██████████| 28/28 [00:05<00:00, 4.88it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 309, title: Save Image, class type: SaveImage Prompt executed in 6.13 seconds outputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== R8_sd3.5L_00001_.pngPrediction
stability-ai/stable-diffusion-3.5-largeOfficial modelIDk8ka8vwc0xrm60cjpj1vj7z6y0StatusSucceededSourceWebTotal durationCreatedInput
- cfg
- 3.5
- steps
- 28
- prompt
- a portrait of a man standing in front of a white wall. His gaze is directed to the right, looking towards something beyond the frame
- aspect_ratio
- 1:1
- output_format
- webp
- output_quality
- 90
{ "cfg": 3.5, "steps": 28, "prompt": "a portrait of a man standing in front of a white wall. His gaze is directed to the right, looking towards something beyond the frame", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { cfg: 3.5, steps: 28, prompt: "a portrait of a man standing in front of a white wall. His gaze is directed to the right, looking towards something beyond the frame", aspect_ratio: "1:1", output_format: "webp", output_quality: 90 }; const output = await replicate.run("stability-ai/stable-diffusion-3.5-large", { input }); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "stability-ai/stable-diffusion-3.5-large", input={ "cfg": 3.5, "steps": 28, "prompt": "a portrait of a man standing in front of a white wall. His gaze is directed to the right, looking towards something beyond the frame", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run stability-ai/stable-diffusion-3.5-large 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 $'{ "input": { "cfg": 3.5, "steps": 28, "prompt": "a portrait of a man standing in front of a white wall. His gaze is directed to the right, looking towards something beyond the frame", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 } }' \ https://api.replicate.com/v1/models/stability-ai/stable-diffusion-3.5-large/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-22T13:56:19.329042Z", "created_at": "2024-10-22T13:56:12.935000Z", "data_removed": false, "error": null, "id": "k8ka8vwc0xrm60cjpj1vj7z6y0", "input": { "cfg": 3.5, "steps": 28, "prompt": "a portrait of a man standing in front of a white wall. His gaze is directed to the right, looking towards something beyond the frame", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90 }, "logs": "Random seed set to: 58550735\nRunning workflow\ngot prompt\nExecuting node 334, title: EmptySD3LatentImage, class type: EmptySD3LatentImage\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 67, title: ConditioningZeroOut, class type: ConditioningZeroOut\nExecuting node 68, title: ConditioningSetTimestepRange, class type: ConditioningSetTimestepRange\nExecuting node 69, title: Conditioning (Combine), class type: ConditioningCombine\nExecuting node 294, title: KSampler, class type: KSampler\n0%| | 0/28 [00:00<?, ?it/s]\n4%|▎ | 1/28 [00:00<00:03, 7.42it/s]\n7%|▋ | 2/28 [00:00<00:05, 4.58it/s]\n11%|█ | 3/28 [00:00<00:05, 4.71it/s]\n14%|█▍ | 4/28 [00:00<00:05, 4.77it/s]\n18%|█▊ | 5/28 [00:01<00:04, 4.81it/s]\n21%|██▏ | 6/28 [00:01<00:04, 4.83it/s]\n25%|██▌ | 7/28 [00:01<00:04, 4.84it/s]\n29%|██▊ | 8/28 [00:01<00:04, 4.85it/s]\n32%|███▏ | 9/28 [00:01<00:03, 4.86it/s]\n36%|███▌ | 10/28 [00:02<00:03, 4.86it/s]\n39%|███▉ | 11/28 [00:02<00:03, 4.87it/s]\n43%|████▎ | 12/28 [00:02<00:03, 4.88it/s]\n46%|████▋ | 13/28 [00:02<00:03, 4.88it/s]\n50%|█████ | 14/28 [00:02<00:02, 4.88it/s]\n54%|█████▎ | 15/28 [00:03<00:02, 4.88it/s]\n57%|█████▋ | 16/28 [00:03<00:02, 4.88it/s]\n61%|██████ | 17/28 [00:03<00:02, 4.87it/s]\n64%|██████▍ | 18/28 [00:03<00:02, 4.87it/s]\n68%|██████▊ | 19/28 [00:03<00:01, 4.87it/s]\n71%|███████▏ | 20/28 [00:04<00:01, 4.87it/s]\n75%|███████▌ | 21/28 [00:04<00:01, 4.87it/s]\n79%|███████▊ | 22/28 [00:04<00:01, 4.87it/s]\n82%|████████▏ | 23/28 [00:04<00:01, 4.87it/s]\n86%|████████▌ | 24/28 [00:04<00:00, 4.87it/s]\n89%|████████▉ | 25/28 [00:05<00:00, 4.87it/s]\n93%|█████████▎| 26/28 [00:05<00:00, 4.87it/s]\n96%|█████████▋| 27/28 [00:05<00:00, 4.87it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.87it/s]\n100%|██████████| 28/28 [00:05<00:00, 4.87it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 309, title: Save Image, class type: SaveImage\nPrompt executed in 6.11 seconds\noutputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8_sd3.5L_00001_.png", "metrics": { "image_count": 1, "predict_time": 6.387730881, "total_time": 6.394042 }, "output": [ "https://replicate.delivery/yhqm/albaypwzh46aJZfq0f9PwosJiPzHB3VAPjFDzik6SPbDEWpTA/R8_sd3.5L_00001_.webp" ], "started_at": "2024-10-22T13:56:12.941311Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/wcdb-hwgfbwm5bl6gzarvb552dks5y7s7qivr7agoz42mhsbs276ybqjq", "get": "https://api.replicate.com/v1/predictions/k8ka8vwc0xrm60cjpj1vj7z6y0", "cancel": "https://api.replicate.com/v1/predictions/k8ka8vwc0xrm60cjpj1vj7z6y0/cancel" }, "version": "hidden" }Generated inRandom seed set to: 58550735 Running workflow got prompt Executing node 334, title: EmptySD3LatentImage, class type: EmptySD3LatentImage Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Executing node 67, title: ConditioningZeroOut, class type: ConditioningZeroOut Executing node 68, title: ConditioningSetTimestepRange, class type: ConditioningSetTimestepRange Executing node 69, title: Conditioning (Combine), class type: ConditioningCombine Executing node 294, title: KSampler, class type: KSampler 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:03, 7.42it/s] 7%|▋ | 2/28 [00:00<00:05, 4.58it/s] 11%|█ | 3/28 [00:00<00:05, 4.71it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.77it/s] 18%|█▊ | 5/28 [00:01<00:04, 4.81it/s] 21%|██▏ | 6/28 [00:01<00:04, 4.83it/s] 25%|██▌ | 7/28 [00:01<00:04, 4.84it/s] 29%|██▊ | 8/28 [00:01<00:04, 4.85it/s] 32%|███▏ | 9/28 [00:01<00:03, 4.86it/s] 36%|███▌ | 10/28 [00:02<00:03, 4.86it/s] 39%|███▉ | 11/28 [00:02<00:03, 4.87it/s] 43%|████▎ | 12/28 [00:02<00:03, 4.88it/s] 46%|████▋ | 13/28 [00:02<00:03, 4.88it/s] 50%|█████ | 14/28 [00:02<00:02, 4.88it/s] 54%|█████▎ | 15/28 [00:03<00:02, 4.88it/s] 57%|█████▋ | 16/28 [00:03<00:02, 4.88it/s] 61%|██████ | 17/28 [00:03<00:02, 4.87it/s] 64%|██████▍ | 18/28 [00:03<00:02, 4.87it/s] 68%|██████▊ | 19/28 [00:03<00:01, 4.87it/s] 71%|███████▏ | 20/28 [00:04<00:01, 4.87it/s] 75%|███████▌ | 21/28 [00:04<00:01, 4.87it/s] 79%|███████▊ | 22/28 [00:04<00:01, 4.87it/s] 82%|████████▏ | 23/28 [00:04<00:01, 4.87it/s] 86%|████████▌ | 24/28 [00:04<00:00, 4.87it/s] 89%|████████▉ | 25/28 [00:05<00:00, 4.87it/s] 93%|█████████▎| 26/28 [00:05<00:00, 4.87it/s] 96%|█████████▋| 27/28 [00:05<00:00, 4.87it/s] 100%|██████████| 28/28 [00:05<00:00, 4.87it/s] 100%|██████████| 28/28 [00:05<00:00, 4.87it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 309, title: Save Image, class type: SaveImage Prompt executed in 6.11 seconds outputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== R8_sd3.5L_00001_.pngPrediction
stability-ai/stable-diffusion-3.5-largeOfficial modelIDam892y5jznrm20cjpm3tc2ms2cStatusSucceededSourceWebTotal durationCreatedInput
- cfg
- 4.5
- steps
- 40
- prompt
- ~*~aesthetic~*~ #boho #fashion, full-body 30-something woman laying on microfloral grass, candid pose, overlay reads Stable Diffusion 3.5, cheerful cursive typography font
- aspect_ratio
- 1:1
- output_format
- webp
- output_quality
- 90
- prompt_strength
- 0.85
{ "cfg": 4.5, "steps": 40, "prompt": "~*~aesthetic~*~ #boho #fashion, full-body 30-something woman laying on microfloral grass, candid pose, overlay reads Stable Diffusion 3.5, cheerful cursive typography font", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90, "prompt_strength": 0.85 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { cfg: 4.5, steps: 40, prompt: "~*~aesthetic~*~ #boho #fashion, full-body 30-something woman laying on microfloral grass, candid pose, overlay reads Stable Diffusion 3.5, cheerful cursive typography font", aspect_ratio: "1:1", output_format: "webp", output_quality: 90, prompt_strength: 0.85 }; const output = await replicate.run("stability-ai/stable-diffusion-3.5-large", { input }); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun stability-ai/stable-diffusion-3.5-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "stability-ai/stable-diffusion-3.5-large", input={ "cfg": 4.5, "steps": 40, "prompt": "~*~aesthetic~*~ #boho #fashion, full-body 30-something woman laying on microfloral grass, candid pose, overlay reads Stable Diffusion 3.5, cheerful cursive typography font", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90, "prompt_strength": 0.85 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run stability-ai/stable-diffusion-3.5-large 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 $'{ "input": { "cfg": 4.5, "steps": 40, "prompt": "~*~aesthetic~*~ #boho #fashion, full-body 30-something woman laying on microfloral grass, candid pose, overlay reads Stable Diffusion 3.5, cheerful cursive typography font", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90, "prompt_strength": 0.85 } }' \ https://api.replicate.com/v1/models/stability-ai/stable-diffusion-3.5-large/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-22T16:20:42.513031Z", "created_at": "2024-10-22T16:20:33.661000Z", "data_removed": false, "error": null, "id": "am892y5jznrm20cjpm3tc2ms2c", "input": { "cfg": 4.5, "steps": 40, "prompt": "~*~aesthetic~*~ #boho #fashion, full-body 30-something woman laying on microfloral grass, candid pose, overlay reads Stable Diffusion 3.5, cheerful cursive typography font", "aspect_ratio": "1:1", "output_format": "webp", "output_quality": 90, "prompt_strength": 0.85 }, "logs": "Seed set to: 3168632025\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 67, title: ConditioningZeroOut, class type: ConditioningZeroOut\nExecuting node 68, title: ConditioningSetTimestepRange, class type: ConditioningSetTimestepRange\nExecuting node 69, title: Conditioning (Combine), class type: ConditioningCombine\nExecuting node 294, title: KSampler, class type: KSampler\n0%| | 0/40 [00:00<?, ?it/s]\n2%|▎ | 1/40 [00:00<00:05, 7.48it/s]\n5%|▌ | 2/40 [00:00<00:08, 4.60it/s]\n8%|▊ | 3/40 [00:00<00:07, 4.71it/s]\n10%|█ | 4/40 [00:00<00:07, 4.77it/s]\n12%|█▎ | 5/40 [00:01<00:07, 4.80it/s]\n15%|█▌ | 6/40 [00:01<00:07, 4.82it/s]\n18%|█▊ | 7/40 [00:01<00:06, 4.83it/s]\n20%|██ | 8/40 [00:01<00:06, 4.84it/s]\n22%|██▎ | 9/40 [00:01<00:06, 4.73it/s]\n25%|██▌ | 10/40 [00:02<00:06, 4.77it/s]\n28%|██▊ | 11/40 [00:02<00:06, 4.79it/s]\n30%|███ | 12/40 [00:02<00:05, 4.81it/s]\n32%|███▎ | 13/40 [00:02<00:05, 4.83it/s]\n35%|███▌ | 14/40 [00:02<00:05, 4.84it/s]\n38%|███▊ | 15/40 [00:03<00:05, 4.84it/s]\n40%|████ | 16/40 [00:03<00:04, 4.84it/s]\n42%|████▎ | 17/40 [00:03<00:04, 4.85it/s]\n45%|████▌ | 18/40 [00:03<00:04, 4.86it/s]\n48%|████▊ | 19/40 [00:03<00:04, 4.86it/s]\n50%|█████ | 20/40 [00:04<00:04, 4.86it/s]\n52%|█████▎ | 21/40 [00:04<00:03, 4.86it/s]\n55%|█████▌ | 22/40 [00:04<00:03, 4.85it/s]\n57%|█████▊ | 23/40 [00:04<00:03, 4.85it/s]\n60%|██████ | 24/40 [00:04<00:03, 4.86it/s]\n62%|██████▎ | 25/40 [00:05<00:03, 4.86it/s]\n65%|██████▌ | 26/40 [00:05<00:02, 4.86it/s]\n68%|██████▊ | 27/40 [00:05<00:02, 4.86it/s]\n70%|███████ | 28/40 [00:05<00:02, 4.86it/s]\n72%|███████▎ | 29/40 [00:05<00:02, 4.85it/s]\n75%|███████▌ | 30/40 [00:06<00:02, 4.85it/s]\n78%|███████▊ | 31/40 [00:06<00:01, 4.86it/s]\n80%|████████ | 32/40 [00:06<00:01, 4.85it/s]\n82%|████████▎ | 33/40 [00:06<00:01, 4.85it/s]\n85%|████████▌ | 34/40 [00:07<00:01, 4.85it/s]\n88%|████████▊ | 35/40 [00:07<00:01, 4.86it/s]\n90%|█████████ | 36/40 [00:07<00:00, 4.85it/s]\n92%|█████████▎| 37/40 [00:07<00:00, 4.86it/s]\n95%|█████████▌| 38/40 [00:07<00:00, 4.85it/s]\n98%|█████████▊| 39/40 [00:08<00:00, 4.85it/s]\n100%|██████████| 40/40 [00:08<00:00, 4.85it/s]\n100%|██████████| 40/40 [00:08<00:00, 4.85it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 309, title: Save Image, class type: SaveImage\nPrompt executed in 8.65 seconds\noutputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8_sd3.5L_00001_.png", "metrics": { "image_count": 1, "predict_time": 8.84619968, "total_time": 8.852031 }, "output": [ "https://replicate.delivery/yhqm/x5swvMgXyDr5JxhAqWf7Sty3YdzweRHHgG6EZA5ndfN0WwSnA/R8_sd3.5L_00001_.webp" ], "started_at": "2024-10-22T16:20:33.666832Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/wcdb-tvf5p7cwhlypjt3472dvzm3kuysuuskvfxlnuqedi4e7mbc6hs3a", "get": "https://api.replicate.com/v1/predictions/am892y5jznrm20cjpm3tc2ms2c", "cancel": "https://api.replicate.com/v1/predictions/am892y5jznrm20cjpm3tc2ms2c/cancel" }, "version": "hidden" }Generated inSeed set to: 3168632025 Running workflow got prompt Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Executing node 67, title: ConditioningZeroOut, class type: ConditioningZeroOut Executing node 68, title: ConditioningSetTimestepRange, class type: ConditioningSetTimestepRange Executing node 69, title: Conditioning (Combine), class type: ConditioningCombine Executing node 294, title: KSampler, class type: KSampler 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:05, 7.48it/s] 5%|▌ | 2/40 [00:00<00:08, 4.60it/s] 8%|▊ | 3/40 [00:00<00:07, 4.71it/s] 10%|█ | 4/40 [00:00<00:07, 4.77it/s] 12%|█▎ | 5/40 [00:01<00:07, 4.80it/s] 15%|█▌ | 6/40 [00:01<00:07, 4.82it/s] 18%|█▊ | 7/40 [00:01<00:06, 4.83it/s] 20%|██ | 8/40 [00:01<00:06, 4.84it/s] 22%|██▎ | 9/40 [00:01<00:06, 4.73it/s] 25%|██▌ | 10/40 [00:02<00:06, 4.77it/s] 28%|██▊ | 11/40 [00:02<00:06, 4.79it/s] 30%|███ | 12/40 [00:02<00:05, 4.81it/s] 32%|███▎ | 13/40 [00:02<00:05, 4.83it/s] 35%|███▌ | 14/40 [00:02<00:05, 4.84it/s] 38%|███▊ | 15/40 [00:03<00:05, 4.84it/s] 40%|████ | 16/40 [00:03<00:04, 4.84it/s] 42%|████▎ | 17/40 [00:03<00:04, 4.85it/s] 45%|████▌ | 18/40 [00:03<00:04, 4.86it/s] 48%|████▊ | 19/40 [00:03<00:04, 4.86it/s] 50%|█████ | 20/40 [00:04<00:04, 4.86it/s] 52%|█████▎ | 21/40 [00:04<00:03, 4.86it/s] 55%|█████▌ | 22/40 [00:04<00:03, 4.85it/s] 57%|█████▊ | 23/40 [00:04<00:03, 4.85it/s] 60%|██████ | 24/40 [00:04<00:03, 4.86it/s] 62%|██████▎ | 25/40 [00:05<00:03, 4.86it/s] 65%|██████▌ | 26/40 [00:05<00:02, 4.86it/s] 68%|██████▊ | 27/40 [00:05<00:02, 4.86it/s] 70%|███████ | 28/40 [00:05<00:02, 4.86it/s] 72%|███████▎ | 29/40 [00:05<00:02, 4.85it/s] 75%|███████▌ | 30/40 [00:06<00:02, 4.85it/s] 78%|███████▊ | 31/40 [00:06<00:01, 4.86it/s] 80%|████████ | 32/40 [00:06<00:01, 4.85it/s] 82%|████████▎ | 33/40 [00:06<00:01, 4.85it/s] 85%|████████▌ | 34/40 [00:07<00:01, 4.85it/s] 88%|████████▊ | 35/40 [00:07<00:01, 4.86it/s] 90%|█████████ | 36/40 [00:07<00:00, 4.85it/s] 92%|█████████▎| 37/40 [00:07<00:00, 4.86it/s] 95%|█████████▌| 38/40 [00:07<00:00, 4.85it/s] 98%|█████████▊| 39/40 [00:08<00:00, 4.85it/s] 100%|██████████| 40/40 [00:08<00:00, 4.85it/s] 100%|██████████| 40/40 [00:08<00:00, 4.85it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 309, title: Save Image, class type: SaveImage Prompt executed in 8.65 seconds outputs: {'309': {'images': [{'filename': 'R8_sd3.5L_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== R8_sd3.5L_00001_.png
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