anotherjesse / sdxl-recur
explore img2img zooming sdxl
- Public
- 1.1K runs
-
L40S
- GitHub
Prediction
anotherjesse/sdxl-recur:9cee5f979f55990d4acb49a9a19553de4d5cedcf0608d1d434e859e734ffb0a8IDvv5vw2lbq63wr7hbdx72ow43neStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- zoom
- 1.05
- image
- steps
- 10
- width
- 1024
- frames
- 20
- height
- 1024
- prompt
- moon rising over clouds and mountains
- scheduler
- K_EULER
- guidance_scale
- 7.5
- negative_prompt
- prompt_strength
- 0.8
{ "zoom": 1.05, "image": "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg", "steps": 10, "width": 1024, "frames": 20, "height": 1024, "prompt": "moon rising over clouds and mountains", "scheduler": "K_EULER", "guidance_scale": 7.5, "negative_prompt": "", "prompt_strength": 0.8 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run anotherjesse/sdxl-recur using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "anotherjesse/sdxl-recur:9cee5f979f55990d4acb49a9a19553de4d5cedcf0608d1d434e859e734ffb0a8", { input: { zoom: 1.05, image: "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg", steps: 10, width: 1024, frames: 20, height: 1024, prompt: "moon rising over clouds and mountains", scheduler: "K_EULER", guidance_scale: 7.5, negative_prompt: "", prompt_strength: 0.8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun anotherjesse/sdxl-recur using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "anotherjesse/sdxl-recur:9cee5f979f55990d4acb49a9a19553de4d5cedcf0608d1d434e859e734ffb0a8", input={ "zoom": 1.05, "image": "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg", "steps": 10, "width": 1024, "frames": 20, "height": 1024, "prompt": "moon rising over clouds and mountains", "scheduler": "K_EULER", "guidance_scale": 7.5, "negative_prompt": "", "prompt_strength": 0.8 } ) # The anotherjesse/sdxl-recur model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/anotherjesse/sdxl-recur/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run anotherjesse/sdxl-recur 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": "anotherjesse/sdxl-recur:9cee5f979f55990d4acb49a9a19553de4d5cedcf0608d1d434e859e734ffb0a8", "input": { "zoom": 1.05, "image": "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg", "steps": 10, "width": 1024, "frames": 20, "height": 1024, "prompt": "moon rising over clouds and mountains", "scheduler": "K_EULER", "guidance_scale": 7.5, "negative_prompt": "", "prompt_strength": 0.8 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-10-10T14:53:27.664546Z", "created_at": "2023-10-10T14:52:51.473981Z", "data_removed": false, "error": null, "id": "vv5vw2lbq63wr7hbdx72ow43ne", "input": { "zoom": 1.05, "image": "https://replicate.delivery/pbxt/JfxDhvZy41TsrWdGz4uO5YUpUQkjnndc57u6FQJuAVXl1RHF/moon.jpg", "steps": 10, "width": 1024, "frames": 20, "height": 1024, "prompt": "moon rising over clouds and mountains", "scheduler": "K_EULER", "guidance_scale": 7.5, "negative_prompt": "", "prompt_strength": 0.8 }, "logs": "Using seed: 37262\n/usr/local/lib/python3.9/site-packages/torch/nn/modules/conv.py:459: UserWarning: Applied workaround for CuDNN issue, install nvrtc.so (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.)\nreturn F.conv2d(input, weight, bias, self.stride,\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:01, 6.01it/s]\n 25%|██▌ | 2/8 [00:00<00:00, 6.35it/s]\n 38%|███▊ | 3/8 [00:00<00:00, 6.48it/s]\n 50%|█████ | 4/8 [00:00<00:00, 6.54it/s]\n 62%|██████▎ | 5/8 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[00:00<00:00, 6.59it/s]\n 75%|███████▌ | 6/8 [00:00<00:00, 6.53it/s]\n 88%|████████▊ | 7/8 [00:01<00:00, 6.53it/s]\n100%|██████████| 8/8 [00:01<00:00, 6.54it/s]\n100%|██████████| 8/8 [00:01<00:00, 6.56it/s]", "metrics": { "predict_time": 35.052018, "total_time": 36.190565 }, "output": [ "https://replicate.delivery/pbxt/VhyqJdVQqnZ5NBhfcmGoi4FXEfx5KKuZ7URplfB1NIUT6iZjA/0000.jpg", "https://replicate.delivery/pbxt/CmiH6XTQeo2JAyA3vcvtDC0D5Kx9t97YhetgO4cQ3fIU6iZjA/0001.jpg", "https://replicate.delivery/pbxt/FWfgxYK1wsVlZaeMKfw8VaswkTMRHabeWeLKLfTyBDebmuY2IA/0002.jpg", "https://replicate.delivery/pbxt/eWgNPUiLGkwATSioOKi0nsO2Qib1oisloxfZkBQeIRod6iZjA/0003.jpg", "https://replicate.delivery/pbxt/jWfWsXr8i815HSkEqFbXs9ta0RLMCcnefFkpei28ufR4pLmNC/0004.jpg", "https://replicate.delivery/pbxt/Gf6o3KmK3cTPNKrS3XYsM8WyZqgFRFRZZSn6lfs2uwLRdxsRA/0005.jpg", "https://replicate.delivery/pbxt/kewn1fsgkgreYJlUed6NyCBlxeb2k41ktmF8pd8G4ATUqLmNC/0006.jpg", "https://replicate.delivery/pbxt/rbCENhVAHF7qG9vbosynZPgHIYqAeIIsMQ5TkE0vnVAquY2IA/0007.jpg", "https://replicate.delivery/pbxt/Ly2o5QBauSpKDZ6rUSOLxrYTHbMn881AMIHjy4X0DeLruY2IA/0008.jpg", "https://replicate.delivery/pbxt/lREuQCqJmFIOIZpvsR77xlMX9efUGVwnI6m3g0XltNzXdxsRA/0009.jpg", "https://replicate.delivery/pbxt/JoIpYgeEd0RgHy2FFBFudkzQ5qX9le4p10PIpOUkdq8ZdxsRA/0010.jpg", "https://replicate.delivery/pbxt/58oLE3VLId7vDhHM8xjRvCgsM9DaXDL5QU1Vc0Ln6zhWXMbE/0011.jpg", "https://replicate.delivery/pbxt/IiVxoYe4lMyXZSi0nCMXKevP3Y5mSAtM2zmxcBVMPpf56iZjA/0012.jpg", "https://replicate.delivery/pbxt/ACh9vROTo9KSBVRgF7NH1Ame1vDkT08cjNGOnIwZfYcddxsRA/0013.jpg", "https://replicate.delivery/pbxt/3APafV9f3NgQv0qcbHpff5ywbI4N9jLbEiQAk1tPyhdfrLmNC/0014.jpg", "https://replicate.delivery/pbxt/Yoaj931WxYpFN9nQpmMsTrzOuMH7MX2gMQWRIoYSloRYXMbE/0015.jpg", "https://replicate.delivery/pbxt/1cc8SmFsyq5cLV2Uo3YLahH1wXHkclHoZPczKA7zrBoYXMbE/0016.jpg", "https://replicate.delivery/pbxt/PcV4xeVK21SCGCrfnyue8Ti8CqSUtU7P9YgqheHa4aTS2FzGB/0017.jpg", "https://replicate.delivery/pbxt/OjkDX05tD7oAI1brzt35Tt2jx3X1OCWVFSDPHnBxJAbZXMbE/0018.jpg", "https://replicate.delivery/pbxt/GaxoRfU77xXBGS4hZEFfYszIy5WOpHAzszZc5JyDUn4ndxsRA/0019.jpg" ], "started_at": "2023-10-10T14:52:52.612528Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vv5vw2lbq63wr7hbdx72ow43ne", "cancel": "https://api.replicate.com/v1/predictions/vv5vw2lbq63wr7hbdx72ow43ne/cancel" }, "version": "9cee5f979f55990d4acb49a9a19553de4d5cedcf0608d1d434e859e734ffb0a8" }Generated inUsing seed: 37262 /usr/local/lib/python3.9/site-packages/torch/nn/modules/conv.py:459: UserWarning: Applied workaround for CuDNN issue, install nvrtc.so (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.) return F.conv2d(input, weight, bias, self.stride, 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:01, 6.01it/s] 25%|██▌ | 2/8 [00:00<00:00, 6.35it/s] 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6.53it/s] 88%|████████▊ | 7/8 [00:01<00:00, 6.54it/s] 100%|██████████| 8/8 [00:01<00:00, 6.56it/s] 100%|██████████| 8/8 [00:01<00:00, 6.57it/s] 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:01, 6.65it/s] 25%|██▌ | 2/8 [00:00<00:00, 6.62it/s] 38%|███▊ | 3/8 [00:00<00:00, 6.61it/s] 50%|█████ | 4/8 [00:00<00:00, 6.60it/s] 62%|██████▎ | 5/8 [00:00<00:00, 6.59it/s] 75%|███████▌ | 6/8 [00:00<00:00, 6.53it/s] 88%|████████▊ | 7/8 [00:01<00:00, 6.53it/s] 100%|██████████| 8/8 [00:01<00:00, 6.54it/s] 100%|██████████| 8/8 [00:01<00:00, 6.57it/s] 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:01, 6.64it/s] 25%|██▌ | 2/8 [00:00<00:00, 6.61it/s] 38%|███▊ | 3/8 [00:00<00:00, 6.59it/s] 50%|█████ | 4/8 [00:00<00:00, 6.59it/s] 62%|██████▎ | 5/8 [00:00<00:00, 6.59it/s] 75%|███████▌ | 6/8 [00:00<00:00, 6.53it/s] 88%|████████▊ | 7/8 [00:01<00:00, 6.53it/s] 100%|██████████| 8/8 [00:01<00:00, 6.54it/s] 100%|██████████| 8/8 [00:01<00:00, 6.56it/s]Prediction
anotherjesse/sdxl-recur:13370d55faee007c6b5cd3d4d66133888308720413f6bdc07cf5439b072c67a1IDzltmx3lbkxsq7w4w4qtsqcoazuStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- zoom
- 1.05
- image
- null
- steps
- 10
- width
- 1024
- frames
- 30
- height
- 1024
- prompt
- mystical macro of molecules
- scheduler
- K_EULER
- guidance_scale
- 7.5
- negative_prompt
- prompt_strength
- 0.8
{ "zoom": 1.05, "image": null, "steps": 10, "width": 1024, "frames": 30, "height": 1024, "prompt": "mystical macro of molecules", "scheduler": "K_EULER", "guidance_scale": 7.5, "negative_prompt": "", "prompt_strength": 0.8 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run anotherjesse/sdxl-recur using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "anotherjesse/sdxl-recur:13370d55faee007c6b5cd3d4d66133888308720413f6bdc07cf5439b072c67a1", { input: { zoom: 1.05, steps: 10, width: 1024, frames: 30, height: 1024, prompt: "mystical macro of molecules", scheduler: "K_EULER", guidance_scale: 7.5, negative_prompt: "", prompt_strength: 0.8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun anotherjesse/sdxl-recur using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "anotherjesse/sdxl-recur:13370d55faee007c6b5cd3d4d66133888308720413f6bdc07cf5439b072c67a1", input={ "zoom": 1.05, "steps": 10, "width": 1024, "frames": 30, "height": 1024, "prompt": "mystical macro of molecules", "scheduler": "K_EULER", "guidance_scale": 7.5, "negative_prompt": "", "prompt_strength": 0.8 } ) # The anotherjesse/sdxl-recur model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/anotherjesse/sdxl-recur/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run anotherjesse/sdxl-recur 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": "anotherjesse/sdxl-recur:13370d55faee007c6b5cd3d4d66133888308720413f6bdc07cf5439b072c67a1", "input": { "zoom": 1.05, "steps": 10, "width": 1024, "frames": 30, "height": 1024, "prompt": "mystical macro of molecules", "scheduler": "K_EULER", "guidance_scale": 7.5, "negative_prompt": "", "prompt_strength": 0.8 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-10-10T15:08:31.338658Z", "created_at": "2023-10-10T15:07:25.161212Z", "data_removed": false, "error": null, "id": "zltmx3lbkxsq7w4w4qtsqcoazu", "input": { "zoom": 1.05, "image": null, "steps": 10, "width": 1024, "frames": 30, "height": 1024, "prompt": "mystical macro of molecules", "scheduler": "K_EULER", "guidance_scale": 7.5, "negative_prompt": "", "prompt_strength": 0.8 }, "logs": "Using seed: 29737\n 0%| | 0/10 [00:00<?, ?it/s]/usr/local/lib/python3.9/site-packages/torch/nn/modules/conv.py:459: UserWarning: Applied workaround for CuDNN issue, install nvrtc.so (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.)\nreturn F.conv2d(input, weight, bias, self.stride,\n 10%|█ | 1/10 [00:00<00:06, 1.32it/s]\n 20%|██ | 2/10 [00:00<00:03, 2.31it/s]\n 30%|███ | 3/10 [00:01<00:02, 3.06it/s]\n 40%|████ | 4/10 [00:01<00:01, 3.60it/s]\n 50%|█████ | 5/10 [00:01<00:01, 3.98it/s]\n 60%|██████ | 6/10 [00:01<00:00, 4.26it/s]\n 70%|███████ | 7/10 [00:01<00:00, 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[00:01<00:00, 4.89it/s]\n 88%|████████▊ | 7/8 [00:01<00:00, 4.89it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.89it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.90it/s]\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:01, 4.93it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 4.92it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 4.91it/s]\n 50%|█████ | 4/8 [00:00<00:00, 4.90it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 4.88it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 4.89it/s]\n 88%|████████▊ | 7/8 [00:01<00:00, 4.89it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.89it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.90it/s]\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:01, 4.92it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 4.90it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 4.90it/s]\n 50%|█████ | 4/8 [00:00<00:00, 4.89it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 4.88it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 4.89it/s]\n 88%|████████▊ | 7/8 [00:01<00:00, 4.89it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.89it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.89it/s]\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:01, 4.93it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 4.92it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 4.91it/s]\n 50%|█████ | 4/8 [00:00<00:00, 4.89it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 4.88it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 4.88it/s]\n 88%|████████▊ | 7/8 [00:01<00:00, 4.89it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.89it/s]\n100%|██████████| 8/8 [00:01<00:00, 4.89it/s]", "metrics": { "predict_time": 64.957709, "total_time": 66.177446 }, "output": [ "https://replicate.delivery/pbxt/9WPk3XQGYqqYMxWaQKsX6ws8j8ITkQHlJzRxKeg1LleyqxsRA/0000.jpg", "https://replicate.delivery/pbxt/GezmAkjG6F2UASzbNK53DT7zyZE2Lo7zpZ0jUgUvu2da1Y2IA/0001.jpg", "https://replicate.delivery/pbxt/fwFUPMzhh8SHKavUDwGbHbexIe47BlfzSDgCKEHq6sf1WNmNC/0002.jpg", "https://replicate.delivery/pbxt/yFULrvXmxnZoKVW0wmnEdedLVclrnVCyA8eXNXWFcBa4qxsRA/0003.jpg", "https://replicate.delivery/pbxt/9Xhcm1SdTErINtLQohfSeFV388CZKABBfzvL1taUGReprGzGB/0004.jpg", 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internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.) return F.conv2d(input, weight, bias, self.stride, 10%|█ | 1/10 [00:00<00:06, 1.32it/s] 20%|██ | 2/10 [00:00<00:03, 2.31it/s] 30%|███ | 3/10 [00:01<00:02, 3.06it/s] 40%|████ | 4/10 [00:01<00:01, 3.60it/s] 50%|█████ | 5/10 [00:01<00:01, 3.98it/s] 60%|██████ | 6/10 [00:01<00:00, 4.26it/s] 70%|███████ | 7/10 [00:01<00:00, 4.46it/s] 80%|████████ | 8/10 [00:02<00:00, 4.60it/s] 90%|█████████ | 9/10 [00:02<00:00, 4.69it/s] 100%|██████████| 10/10 [00:02<00:00, 4.76it/s] 100%|██████████| 10/10 [00:02<00:00, 3.87it/s] 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:01, 4.93it/s] 25%|██▌ | 2/8 [00:00<00:01, 4.93it/s] 38%|███▊ | 3/8 [00:00<00:01, 4.92it/s] 50%|█████ | 4/8 [00:00<00:00, 4.92it/s] 62%|██████▎ | 5/8 [00:01<00:00, 4.92it/s] 75%|███████▌ | 6/8 [00:01<00:00, 4.92it/s] 88%|████████▊ | 7/8 [00:01<00:00, 4.92it/s] 100%|██████████| 8/8 [00:01<00:00, 4.91it/s] 100%|██████████| 8/8 [00:01<00:00, 4.92it/s] 0%| | 0/8 [00:00<?, ?it/s] 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