lucataco / realvisxl-v2.0
Implementation of SDXL RealVisXL_V2.0
Prediction
lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4fIDunrmhgdb2ma5eh2uu2xcqf4ekmStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- seed
- 2020353893
- width
- 1024
- height
- 1024
- prompt
- front shot, portrait photo of a cute 22 y.o woman, looks away, full lips, natural skin, skin moles, stormy weather, (cinematic, film grain:1.1)
- scheduler
- DPMSolverMultistep
- guidance_scale
- 7
- negative_prompt
- (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth
- num_inference_steps
- 40
{ "seed": 2020353893, "width": 1024, "height": 1024, "prompt": "front shot, portrait photo of a cute 22 y.o woman, looks away, full lips, natural skin, skin moles, stormy weather, (cinematic, film grain:1.1)", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", { input: { seed: 2020353893, width: 1024, height: 1024, prompt: "front shot, portrait photo of a cute 22 y.o woman, looks away, full lips, natural skin, skin moles, stormy weather, (cinematic, film grain:1.1)", scheduler: "DPMSolverMultistep", guidance_scale: 7, negative_prompt: "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", num_inference_steps: 40 } } ); // 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 replicateImport the client:import replicateRun lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", input={ "seed": 2020353893, "width": 1024, "height": 1024, "prompt": "front shot, portrait photo of a cute 22 y.o woman, looks away, full lips, natural skin, skin moles, stormy weather, (cinematic, film grain:1.1)", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/realvisxl-v2.0 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": "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", "input": { "seed": 2020353893, "width": 1024, "height": 1024, "prompt": "front shot, portrait photo of a cute 22 y.o woman, looks away, full lips, natural skin, skin moles, stormy weather, (cinematic, film grain:1.1)", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-01T15:13:37.910792Z", "created_at": "2023-11-01T15:13:28.000386Z", "data_removed": false, "error": null, "id": "unrmhgdb2ma5eh2uu2xcqf4ekm", "input": { "seed": 2020353893, "width": 1024, "height": 1024, "prompt": "front shot, portrait photo of a cute 22 y.o woman, looks away, full lips, natural skin, skin moles, stormy weather, (cinematic, film grain:1.1)", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 }, "logs": "Using seed: 2020353893\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:07, 5.06it/s]\n 5%|▌ | 2/40 [00:00<00:07, 5.03it/s]\n 8%|▊ | 3/40 [00:00<00:07, 5.02it/s]\n 10%|█ | 4/40 [00:00<00:07, 5.01it/s]\n 12%|█▎ | 5/40 [00:00<00:06, 5.01it/s]\n 15%|█▌ | 6/40 [00:01<00:06, 5.02it/s]\n 18%|█▊ | 7/40 [00:01<00:06, 5.03it/s]\n 20%|██ | 8/40 [00:01<00:06, 5.03it/s]\n 22%|██▎ | 9/40 [00:01<00:06, 5.03it/s]\n 25%|██▌ | 10/40 [00:01<00:05, 5.03it/s]\n 28%|██▊ | 11/40 [00:02<00:05, 5.03it/s]\n 30%|███ | 12/40 [00:02<00:05, 5.03it/s]\n 32%|███▎ | 13/40 [00:02<00:05, 5.03it/s]\n 35%|███▌ | 14/40 [00:02<00:05, 5.03it/s]\n 38%|███▊ | 15/40 [00:02<00:04, 5.03it/s]\n 40%|████ | 16/40 [00:03<00:04, 5.03it/s]\n 42%|████▎ | 17/40 [00:03<00:04, 5.03it/s]\n 45%|████▌ | 18/40 [00:03<00:04, 5.03it/s]\n 48%|████▊ | 19/40 [00:03<00:04, 5.03it/s]\n 50%|█████ | 20/40 [00:03<00:03, 5.02it/s]\n 52%|█████▎ | 21/40 [00:04<00:03, 5.01it/s]\n 55%|█████▌ | 22/40 [00:04<00:03, 5.01it/s]\n 57%|█████▊ | 23/40 [00:04<00:03, 5.01it/s]\n 60%|██████ | 24/40 [00:04<00:03, 5.01it/s]\n 62%|██████▎ | 25/40 [00:04<00:02, 5.01it/s]\n 65%|██████▌ | 26/40 [00:05<00:02, 5.01it/s]\n 68%|██████▊ | 27/40 [00:05<00:02, 5.01it/s]\n 70%|███████ | 28/40 [00:05<00:02, 5.01it/s]\n 72%|███████▎ | 29/40 [00:05<00:02, 5.01it/s]\n 75%|███████▌ | 30/40 [00:05<00:01, 5.01it/s]\n 78%|███████▊ | 31/40 [00:06<00:01, 5.01it/s]\n 80%|████████ | 32/40 [00:06<00:01, 5.00it/s]\n 82%|████████▎ | 33/40 [00:06<00:01, 5.01it/s]\n 85%|████████▌ | 34/40 [00:06<00:01, 5.01it/s]\n 88%|████████▊ | 35/40 [00:06<00:00, 5.01it/s]\n 90%|█████████ | 36/40 [00:07<00:00, 5.01it/s]\n 92%|█████████▎| 37/40 [00:07<00:00, 4.95it/s]\n 95%|█████████▌| 38/40 [00:07<00:00, 4.95it/s]\n 98%|█████████▊| 39/40 [00:07<00:00, 4.96it/s]\n100%|██████████| 40/40 [00:07<00:00, 4.97it/s]\n100%|██████████| 40/40 [00:07<00:00, 5.01it/s]", "metrics": { "predict_time": 9.893207, "total_time": 9.910406 }, "output": "https://replicate.delivery/pbxt/WRBpX6pWYC6uG57BVF3rgxzvg4U0ZROvngw8CyIpbBOIdAdE/output.png", "started_at": "2023-11-01T15:13:28.017585Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/unrmhgdb2ma5eh2uu2xcqf4ekm", "cancel": "https://api.replicate.com/v1/predictions/unrmhgdb2ma5eh2uu2xcqf4ekm/cancel" }, "version": "902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f" }Generated inUsing seed: 2020353893 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:07, 5.06it/s] 5%|▌ | 2/40 [00:00<00:07, 5.03it/s] 8%|▊ | 3/40 [00:00<00:07, 5.02it/s] 10%|█ | 4/40 [00:00<00:07, 5.01it/s] 12%|█▎ | 5/40 [00:00<00:06, 5.01it/s] 15%|█▌ | 6/40 [00:01<00:06, 5.02it/s] 18%|█▊ | 7/40 [00:01<00:06, 5.03it/s] 20%|██ | 8/40 [00:01<00:06, 5.03it/s] 22%|██▎ | 9/40 [00:01<00:06, 5.03it/s] 25%|██▌ | 10/40 [00:01<00:05, 5.03it/s] 28%|██▊ | 11/40 [00:02<00:05, 5.03it/s] 30%|███ | 12/40 [00:02<00:05, 5.03it/s] 32%|███▎ | 13/40 [00:02<00:05, 5.03it/s] 35%|███▌ | 14/40 [00:02<00:05, 5.03it/s] 38%|███▊ | 15/40 [00:02<00:04, 5.03it/s] 40%|████ | 16/40 [00:03<00:04, 5.03it/s] 42%|████▎ | 17/40 [00:03<00:04, 5.03it/s] 45%|████▌ | 18/40 [00:03<00:04, 5.03it/s] 48%|████▊ | 19/40 [00:03<00:04, 5.03it/s] 50%|█████ | 20/40 [00:03<00:03, 5.02it/s] 52%|█████▎ | 21/40 [00:04<00:03, 5.01it/s] 55%|█████▌ | 22/40 [00:04<00:03, 5.01it/s] 57%|█████▊ | 23/40 [00:04<00:03, 5.01it/s] 60%|██████ | 24/40 [00:04<00:03, 5.01it/s] 62%|██████▎ | 25/40 [00:04<00:02, 5.01it/s] 65%|██████▌ | 26/40 [00:05<00:02, 5.01it/s] 68%|██████▊ | 27/40 [00:05<00:02, 5.01it/s] 70%|███████ | 28/40 [00:05<00:02, 5.01it/s] 72%|███████▎ | 29/40 [00:05<00:02, 5.01it/s] 75%|███████▌ | 30/40 [00:05<00:01, 5.01it/s] 78%|███████▊ | 31/40 [00:06<00:01, 5.01it/s] 80%|████████ | 32/40 [00:06<00:01, 5.00it/s] 82%|████████▎ | 33/40 [00:06<00:01, 5.01it/s] 85%|████████▌ | 34/40 [00:06<00:01, 5.01it/s] 88%|████████▊ | 35/40 [00:06<00:00, 5.01it/s] 90%|█████████ | 36/40 [00:07<00:00, 5.01it/s] 92%|█████████▎| 37/40 [00:07<00:00, 4.95it/s] 95%|█████████▌| 38/40 [00:07<00:00, 4.95it/s] 98%|█████████▊| 39/40 [00:07<00:00, 4.96it/s] 100%|██████████| 40/40 [00:07<00:00, 4.97it/s] 100%|██████████| 40/40 [00:07<00:00, 5.01it/s]Prediction
lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4fIDabb4dp3bej56l7xvaevajhdph4StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- seed
- 1111316860
- width
- 1024
- height
- 1024
- prompt
- dark shot, front shot, closeup photo of a 25 y.o man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot
- scheduler
- DPMSolverMultistep
- guidance_scale
- 7
- negative_prompt
- (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth
- num_inference_steps
- 40
{ "seed": 1111316860, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", { input: { seed: 1111316860, width: 1024, height: 1024, prompt: "dark shot, front shot, closeup photo of a 25 y.o man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", scheduler: "DPMSolverMultistep", guidance_scale: 7, negative_prompt: "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", num_inference_steps: 40 } } ); // 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 replicateImport the client:import replicateRun lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", input={ "seed": 1111316860, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/realvisxl-v2.0 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": "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", "input": { "seed": 1111316860, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-01T15:15:30.798354Z", "created_at": "2023-11-01T15:15:21.132855Z", "data_removed": false, "error": null, "id": "abb4dp3bej56l7xvaevajhdph4", "input": { "seed": 1111316860, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 }, "logs": "Using seed: 1111316860\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:07, 5.08it/s]\n 5%|▌ | 2/40 [00:00<00:07, 5.05it/s]\n 8%|▊ | 3/40 [00:00<00:07, 5.04it/s]\n 10%|█ | 4/40 [00:00<00:07, 5.05it/s]\n 12%|█▎ | 5/40 [00:00<00:06, 5.05it/s]\n 15%|█▌ | 6/40 [00:01<00:06, 5.05it/s]\n 18%|█▊ | 7/40 [00:01<00:06, 5.05it/s]\n 20%|██ | 8/40 [00:01<00:06, 5.04it/s]\n 22%|██▎ | 9/40 [00:01<00:06, 5.04it/s]\n 25%|██▌ | 10/40 [00:01<00:05, 5.03it/s]\n 28%|██▊ | 11/40 [00:02<00:05, 5.04it/s]\n 30%|███ | 12/40 [00:02<00:05, 5.03it/s]\n 32%|███▎ | 13/40 [00:02<00:05, 5.03it/s]\n 35%|███▌ | 14/40 [00:02<00:05, 5.03it/s]\n 38%|███▊ | 15/40 [00:02<00:04, 5.03it/s]\n 40%|████ | 16/40 [00:03<00:04, 5.03it/s]\n 42%|████▎ | 17/40 [00:03<00:04, 5.03it/s]\n 45%|████▌ | 18/40 [00:03<00:04, 5.03it/s]\n 48%|████▊ | 19/40 [00:03<00:04, 5.03it/s]\n 50%|█████ | 20/40 [00:03<00:03, 5.03it/s]\n 52%|█████▎ | 21/40 [00:04<00:03, 5.04it/s]\n 55%|█████▌ | 22/40 [00:04<00:03, 5.04it/s]\n 57%|█████▊ | 23/40 [00:04<00:03, 5.04it/s]\n 60%|██████ | 24/40 [00:04<00:03, 5.03it/s]\n 62%|██████▎ | 25/40 [00:04<00:02, 5.02it/s]\n 65%|██████▌ | 26/40 [00:05<00:02, 5.02it/s]\n 68%|██████▊ | 27/40 [00:05<00:02, 5.02it/s]\n 70%|███████ | 28/40 [00:05<00:02, 5.01it/s]\n 72%|███████▎ | 29/40 [00:05<00:02, 5.01it/s]\n 75%|███████▌ | 30/40 [00:05<00:01, 5.01it/s]\n 78%|███████▊ | 31/40 [00:06<00:01, 5.01it/s]\n 80%|████████ | 32/40 [00:06<00:01, 5.01it/s]\n 82%|████████▎ | 33/40 [00:06<00:01, 5.01it/s]\n 85%|████████▌ | 34/40 [00:06<00:01, 5.00it/s]\n 88%|████████▊ | 35/40 [00:06<00:01, 5.00it/s]\n 90%|█████████ | 36/40 [00:07<00:00, 5.00it/s]\n 92%|█████████▎| 37/40 [00:07<00:00, 5.00it/s]\n 95%|█████████▌| 38/40 [00:07<00:00, 5.00it/s]\n 98%|█████████▊| 39/40 [00:07<00:00, 5.00it/s]\n100%|██████████| 40/40 [00:07<00:00, 5.00it/s]\n100%|██████████| 40/40 [00:07<00:00, 5.02it/s]", "metrics": { "predict_time": 9.774725, "total_time": 9.665499 }, "output": "https://replicate.delivery/pbxt/7TKT7Z6GyF77LhefAlIt4tPWHcXAz9nfUfVMJ2NzcUcEZHQHB/output.png", "started_at": "2023-11-01T15:15:21.023629Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/abb4dp3bej56l7xvaevajhdph4", "cancel": "https://api.replicate.com/v1/predictions/abb4dp3bej56l7xvaevajhdph4/cancel" }, "version": "902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f" }Generated inUsing seed: 1111316860 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:07, 5.08it/s] 5%|▌ | 2/40 [00:00<00:07, 5.05it/s] 8%|▊ | 3/40 [00:00<00:07, 5.04it/s] 10%|█ | 4/40 [00:00<00:07, 5.05it/s] 12%|█▎ | 5/40 [00:00<00:06, 5.05it/s] 15%|█▌ | 6/40 [00:01<00:06, 5.05it/s] 18%|█▊ | 7/40 [00:01<00:06, 5.05it/s] 20%|██ | 8/40 [00:01<00:06, 5.04it/s] 22%|██▎ | 9/40 [00:01<00:06, 5.04it/s] 25%|██▌ | 10/40 [00:01<00:05, 5.03it/s] 28%|██▊ | 11/40 [00:02<00:05, 5.04it/s] 30%|███ | 12/40 [00:02<00:05, 5.03it/s] 32%|███▎ | 13/40 [00:02<00:05, 5.03it/s] 35%|███▌ | 14/40 [00:02<00:05, 5.03it/s] 38%|███▊ | 15/40 [00:02<00:04, 5.03it/s] 40%|████ | 16/40 [00:03<00:04, 5.03it/s] 42%|████▎ | 17/40 [00:03<00:04, 5.03it/s] 45%|████▌ | 18/40 [00:03<00:04, 5.03it/s] 48%|████▊ | 19/40 [00:03<00:04, 5.03it/s] 50%|█████ | 20/40 [00:03<00:03, 5.03it/s] 52%|█████▎ | 21/40 [00:04<00:03, 5.04it/s] 55%|█████▌ | 22/40 [00:04<00:03, 5.04it/s] 57%|█████▊ | 23/40 [00:04<00:03, 5.04it/s] 60%|██████ | 24/40 [00:04<00:03, 5.03it/s] 62%|██████▎ | 25/40 [00:04<00:02, 5.02it/s] 65%|██████▌ | 26/40 [00:05<00:02, 5.02it/s] 68%|██████▊ | 27/40 [00:05<00:02, 5.02it/s] 70%|███████ | 28/40 [00:05<00:02, 5.01it/s] 72%|███████▎ | 29/40 [00:05<00:02, 5.01it/s] 75%|███████▌ | 30/40 [00:05<00:01, 5.01it/s] 78%|███████▊ | 31/40 [00:06<00:01, 5.01it/s] 80%|████████ | 32/40 [00:06<00:01, 5.01it/s] 82%|████████▎ | 33/40 [00:06<00:01, 5.01it/s] 85%|████████▌ | 34/40 [00:06<00:01, 5.00it/s] 88%|████████▊ | 35/40 [00:06<00:01, 5.00it/s] 90%|█████████ | 36/40 [00:07<00:00, 5.00it/s] 92%|█████████▎| 37/40 [00:07<00:00, 5.00it/s] 95%|█████████▌| 38/40 [00:07<00:00, 5.00it/s] 98%|█████████▊| 39/40 [00:07<00:00, 5.00it/s] 100%|██████████| 40/40 [00:07<00:00, 5.00it/s] 100%|██████████| 40/40 [00:07<00:00, 5.02it/s]Prediction
lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4fIDsoz7t6db2rtbbdnwqiqmzm2wx4StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- seed
- 1111316860
- width
- 1024
- height
- 1024
- prompt
- dark shot, front shot, closeup photo of a 25 y.o latina woman, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot
- scheduler
- DPMSolverMultistep
- guidance_scale
- 7
- negative_prompt
- (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth
- num_inference_steps
- 40
{ "seed": 1111316860, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o latina woman, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", { input: { seed: 1111316860, width: 1024, height: 1024, prompt: "dark shot, front shot, closeup photo of a 25 y.o latina woman, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", scheduler: "DPMSolverMultistep", guidance_scale: 7, negative_prompt: "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", num_inference_steps: 40 } } ); // 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 replicateImport the client:import replicateRun lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", input={ "seed": 1111316860, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o latina woman, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/realvisxl-v2.0 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": "lucataco/realvisxl-v2.0:902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f", "input": { "seed": 1111316860, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o latina woman, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-01T15:15:57.314955Z", "created_at": "2023-11-01T15:15:47.473277Z", "data_removed": false, "error": null, "id": "soz7t6db2rtbbdnwqiqmzm2wx4", "input": { "seed": 1111316860, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o latina woman, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 }, "logs": "Using seed: 1111316860\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:07, 5.07it/s]\n 5%|▌ | 2/40 [00:00<00:07, 5.05it/s]\n 8%|▊ | 3/40 [00:00<00:07, 5.04it/s]\n 10%|█ | 4/40 [00:00<00:07, 5.04it/s]\n 12%|█▎ | 5/40 [00:00<00:06, 5.04it/s]\n 15%|█▌ | 6/40 [00:01<00:06, 5.04it/s]\n 18%|█▊ | 7/40 [00:01<00:06, 5.03it/s]\n 20%|██ | 8/40 [00:01<00:06, 5.03it/s]\n 22%|██▎ | 9/40 [00:01<00:06, 5.03it/s]\n 25%|██▌ | 10/40 [00:01<00:05, 5.02it/s]\n 28%|██▊ | 11/40 [00:02<00:05, 5.02it/s]\n 30%|███ | 12/40 [00:02<00:05, 5.02it/s]\n 32%|███▎ | 13/40 [00:02<00:05, 5.02it/s]\n 35%|███▌ | 14/40 [00:02<00:05, 5.01it/s]\n 38%|███▊ | 15/40 [00:02<00:04, 5.01it/s]\n 40%|████ | 16/40 [00:03<00:04, 5.01it/s]\n 42%|████▎ | 17/40 [00:03<00:04, 5.01it/s]\n 45%|████▌ | 18/40 [00:03<00:04, 5.01it/s]\n 48%|████▊ | 19/40 [00:03<00:04, 5.00it/s]\n 50%|█████ | 20/40 [00:03<00:04, 4.99it/s]\n 52%|█████▎ | 21/40 [00:04<00:03, 5.00it/s]\n 55%|█████▌ | 22/40 [00:04<00:03, 5.00it/s]\n 57%|█████▊ | 23/40 [00:04<00:03, 5.00it/s]\n 60%|██████ | 24/40 [00:04<00:03, 5.00it/s]\n 62%|██████▎ | 25/40 [00:04<00:03, 5.00it/s]\n 65%|██████▌ | 26/40 [00:05<00:02, 5.00it/s]\n 68%|██████▊ | 27/40 [00:05<00:02, 5.00it/s]\n 70%|███████ | 28/40 [00:05<00:02, 5.00it/s]\n 72%|███████▎ | 29/40 [00:05<00:02, 5.00it/s]\n 75%|███████▌ | 30/40 [00:05<00:02, 5.00it/s]\n 78%|███████▊ | 31/40 [00:06<00:01, 4.99it/s]\n 80%|████████ | 32/40 [00:06<00:01, 4.99it/s]\n 82%|████████▎ | 33/40 [00:06<00:01, 4.99it/s]\n 85%|████████▌ | 34/40 [00:06<00:01, 4.99it/s]\n 88%|████████▊ | 35/40 [00:06<00:01, 4.99it/s]\n 90%|█████████ | 36/40 [00:07<00:00, 4.99it/s]\n 92%|█████████▎| 37/40 [00:07<00:00, 4.99it/s]\n 95%|█████████▌| 38/40 [00:07<00:00, 4.99it/s]\n 98%|█████████▊| 39/40 [00:07<00:00, 4.99it/s]\n100%|██████████| 40/40 [00:07<00:00, 4.99it/s]\n100%|██████████| 40/40 [00:07<00:00, 5.01it/s]", "metrics": { "predict_time": 9.882817, "total_time": 9.841678 }, "output": "https://replicate.delivery/pbxt/swQcxNpx0PY1PNNuMiLvIiXiJzL0K1wLhGUhbUkZtpBrdAdE/output.png", "started_at": "2023-11-01T15:15:47.432138Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/soz7t6db2rtbbdnwqiqmzm2wx4", "cancel": "https://api.replicate.com/v1/predictions/soz7t6db2rtbbdnwqiqmzm2wx4/cancel" }, "version": "902ae0564a83553dda805027998af32830bcae881ab702d50f54d6415cdd8d4f" }Generated inUsing seed: 1111316860 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:07, 5.07it/s] 5%|▌ | 2/40 [00:00<00:07, 5.05it/s] 8%|▊ | 3/40 [00:00<00:07, 5.04it/s] 10%|█ | 4/40 [00:00<00:07, 5.04it/s] 12%|█▎ | 5/40 [00:00<00:06, 5.04it/s] 15%|█▌ | 6/40 [00:01<00:06, 5.04it/s] 18%|█▊ | 7/40 [00:01<00:06, 5.03it/s] 20%|██ | 8/40 [00:01<00:06, 5.03it/s] 22%|██▎ | 9/40 [00:01<00:06, 5.03it/s] 25%|██▌ | 10/40 [00:01<00:05, 5.02it/s] 28%|██▊ | 11/40 [00:02<00:05, 5.02it/s] 30%|███ | 12/40 [00:02<00:05, 5.02it/s] 32%|███▎ | 13/40 [00:02<00:05, 5.02it/s] 35%|███▌ | 14/40 [00:02<00:05, 5.01it/s] 38%|███▊ | 15/40 [00:02<00:04, 5.01it/s] 40%|████ | 16/40 [00:03<00:04, 5.01it/s] 42%|████▎ | 17/40 [00:03<00:04, 5.01it/s] 45%|████▌ | 18/40 [00:03<00:04, 5.01it/s] 48%|████▊ | 19/40 [00:03<00:04, 5.00it/s] 50%|█████ | 20/40 [00:03<00:04, 4.99it/s] 52%|█████▎ | 21/40 [00:04<00:03, 5.00it/s] 55%|█████▌ | 22/40 [00:04<00:03, 5.00it/s] 57%|█████▊ | 23/40 [00:04<00:03, 5.00it/s] 60%|██████ | 24/40 [00:04<00:03, 5.00it/s] 62%|██████▎ | 25/40 [00:04<00:03, 5.00it/s] 65%|██████▌ | 26/40 [00:05<00:02, 5.00it/s] 68%|██████▊ | 27/40 [00:05<00:02, 5.00it/s] 70%|███████ | 28/40 [00:05<00:02, 5.00it/s] 72%|███████▎ | 29/40 [00:05<00:02, 5.00it/s] 75%|███████▌ | 30/40 [00:05<00:02, 5.00it/s] 78%|███████▊ | 31/40 [00:06<00:01, 4.99it/s] 80%|████████ | 32/40 [00:06<00:01, 4.99it/s] 82%|████████▎ | 33/40 [00:06<00:01, 4.99it/s] 85%|████████▌ | 34/40 [00:06<00:01, 4.99it/s] 88%|████████▊ | 35/40 [00:06<00:01, 4.99it/s] 90%|█████████ | 36/40 [00:07<00:00, 4.99it/s] 92%|█████████▎| 37/40 [00:07<00:00, 4.99it/s] 95%|█████████▌| 38/40 [00:07<00:00, 4.99it/s] 98%|█████████▊| 39/40 [00:07<00:00, 4.99it/s] 100%|██████████| 40/40 [00:07<00:00, 4.99it/s] 100%|██████████| 40/40 [00:07<00:00, 5.01it/s]Prediction
lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08IDlof36hlbixwbzssmddjlk2voneStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- seed
- 1111316861
- width
- 1024
- height
- 1024
- prompt
- dark shot, front shot, closeup photo of a 25 y.o latino man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot
- scheduler
- DPMSolverMultistep
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7
- apply_watermark
- negative_prompt
- (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth
- prompt_strength
- 0.8
- num_inference_steps
- 40
{ "seed": 1111316861, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o latino man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", { input: { seed: 1111316861, width: 1024, height: 1024, prompt: "dark shot, front shot, closeup photo of a 25 y.o latino man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", scheduler: "DPMSolverMultistep", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7, apply_watermark: true, negative_prompt: "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", prompt_strength: 0.8, num_inference_steps: 40 } } ); // 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 lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", input={ "seed": 1111316861, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o latino man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7, "apply_watermark": True, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/realvisxl-v2.0 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": "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", "input": { "seed": 1111316861, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o latino man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-09T14:55:25.568927Z", "created_at": "2023-11-09T14:54:00.812301Z", "data_removed": false, "error": null, "id": "lof36hlbixwbzssmddjlk2vone", "input": { "seed": 1111316861, "width": 1024, "height": 1024, "prompt": "dark shot, front shot, closeup photo of a 25 y.o latino man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 }, "logs": "Using seed: 1111316861\nPrompt: dark shot, front shot, closeup photo of a 25 y.o latino man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot\ntxt2img mode\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:30, 1.29it/s]\n 5%|▌ | 2/40 [00:00<00:16, 2.29it/s]\n 8%|▊ | 3/40 [00:01<00:12, 3.04it/s]\n 10%|█ | 4/40 [00:01<00:10, 3.60it/s]\n 12%|█▎ | 5/40 [00:01<00:08, 3.98it/s]\n 15%|█▌ | 6/40 [00:01<00:07, 4.27it/s]\n 18%|█▊ | 7/40 [00:01<00:07, 4.48it/s]\n 20%|██ | 8/40 [00:02<00:06, 4.62it/s]\n 22%|██▎ | 9/40 [00:02<00:06, 4.73it/s]\n 25%|██▌ | 10/40 [00:02<00:06, 4.79it/s]\n 28%|██▊ | 11/40 [00:02<00:05, 4.83it/s]\n 30%|███ | 12/40 [00:02<00:05, 4.87it/s]\n 32%|███▎ | 13/40 [00:03<00:05, 4.89it/s]\n 35%|███▌ | 14/40 [00:03<00:05, 4.91it/s]\n 38%|███▊ | 15/40 [00:03<00:05, 4.92it/s]\n 40%|████ | 16/40 [00:03<00:04, 4.93it/s]\n 42%|████▎ | 17/40 [00:04<00:04, 4.93it/s]\n 45%|████▌ | 18/40 [00:04<00:04, 4.93it/s]\n 48%|████▊ | 19/40 [00:04<00:04, 4.93it/s]\n 50%|█████ | 20/40 [00:04<00:04, 4.94it/s]\n 52%|█████▎ | 21/40 [00:04<00:03, 4.94it/s]\n 55%|█████▌ | 22/40 [00:05<00:03, 4.94it/s]\n 57%|█████▊ | 23/40 [00:05<00:03, 4.93it/s]\n 60%|██████ | 24/40 [00:05<00:03, 4.94it/s]\n 62%|██████▎ | 25/40 [00:05<00:03, 4.94it/s]\n 65%|██████▌ | 26/40 [00:05<00:02, 4.93it/s]\n 68%|██████▊ | 27/40 [00:06<00:02, 4.93it/s]\n 70%|███████ | 28/40 [00:06<00:02, 4.93it/s]\n 72%|███████▎ | 29/40 [00:06<00:02, 4.93it/s]\n 75%|███████▌ | 30/40 [00:06<00:02, 4.93it/s]\n 78%|███████▊ | 31/40 [00:06<00:01, 4.93it/s]\n 80%|████████ | 32/40 [00:07<00:01, 4.93it/s]\n 82%|████████▎ | 33/40 [00:07<00:01, 4.92it/s]\n 85%|████████▌ | 34/40 [00:07<00:01, 4.92it/s]\n 88%|████████▊ | 35/40 [00:07<00:01, 4.92it/s]\n 90%|█████████ | 36/40 [00:07<00:00, 4.92it/s]\n 92%|█████████▎| 37/40 [00:08<00:00, 4.92it/s]\n 95%|█████████▌| 38/40 [00:08<00:00, 4.93it/s]\n 98%|█████████▊| 39/40 [00:08<00:00, 4.92it/s]\n100%|██████████| 40/40 [00:08<00:00, 4.93it/s]\n100%|██████████| 40/40 [00:08<00:00, 4.61it/s]", "metrics": { "predict_time": 10.659223, "total_time": 84.756626 }, "output": [ "https://replicate.delivery/pbxt/eCTbwmWQ00UbQiZdRMfgLhTRIKFUkBPei9fOQ2taGKw3NpaHB/out-0.png" ], "started_at": "2023-11-09T14:55:14.909704Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/lof36hlbixwbzssmddjlk2vone", "cancel": "https://api.replicate.com/v1/predictions/lof36hlbixwbzssmddjlk2vone/cancel" }, "version": "7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08" }Generated inUsing seed: 1111316861 Prompt: dark shot, front shot, closeup photo of a 25 y.o latino man, perfect eyes, natural skin, skin moles, looks at viewer, cinematic shot txt2img mode 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:30, 1.29it/s] 5%|▌ | 2/40 [00:00<00:16, 2.29it/s] 8%|▊ | 3/40 [00:01<00:12, 3.04it/s] 10%|█ | 4/40 [00:01<00:10, 3.60it/s] 12%|█▎ | 5/40 [00:01<00:08, 3.98it/s] 15%|█▌ | 6/40 [00:01<00:07, 4.27it/s] 18%|█▊ | 7/40 [00:01<00:07, 4.48it/s] 20%|██ | 8/40 [00:02<00:06, 4.62it/s] 22%|██▎ | 9/40 [00:02<00:06, 4.73it/s] 25%|██▌ | 10/40 [00:02<00:06, 4.79it/s] 28%|██▊ | 11/40 [00:02<00:05, 4.83it/s] 30%|███ | 12/40 [00:02<00:05, 4.87it/s] 32%|███▎ | 13/40 [00:03<00:05, 4.89it/s] 35%|███▌ | 14/40 [00:03<00:05, 4.91it/s] 38%|███▊ | 15/40 [00:03<00:05, 4.92it/s] 40%|████ | 16/40 [00:03<00:04, 4.93it/s] 42%|████▎ | 17/40 [00:04<00:04, 4.93it/s] 45%|████▌ | 18/40 [00:04<00:04, 4.93it/s] 48%|████▊ | 19/40 [00:04<00:04, 4.93it/s] 50%|█████ | 20/40 [00:04<00:04, 4.94it/s] 52%|█████▎ | 21/40 [00:04<00:03, 4.94it/s] 55%|█████▌ | 22/40 [00:05<00:03, 4.94it/s] 57%|█████▊ | 23/40 [00:05<00:03, 4.93it/s] 60%|██████ | 24/40 [00:05<00:03, 4.94it/s] 62%|██████▎ | 25/40 [00:05<00:03, 4.94it/s] 65%|██████▌ | 26/40 [00:05<00:02, 4.93it/s] 68%|██████▊ | 27/40 [00:06<00:02, 4.93it/s] 70%|███████ | 28/40 [00:06<00:02, 4.93it/s] 72%|███████▎ | 29/40 [00:06<00:02, 4.93it/s] 75%|███████▌ | 30/40 [00:06<00:02, 4.93it/s] 78%|███████▊ | 31/40 [00:06<00:01, 4.93it/s] 80%|████████ | 32/40 [00:07<00:01, 4.93it/s] 82%|████████▎ | 33/40 [00:07<00:01, 4.92it/s] 85%|████████▌ | 34/40 [00:07<00:01, 4.92it/s] 88%|████████▊ | 35/40 [00:07<00:01, 4.92it/s] 90%|█████████ | 36/40 [00:07<00:00, 4.92it/s] 92%|█████████▎| 37/40 [00:08<00:00, 4.92it/s] 95%|█████████▌| 38/40 [00:08<00:00, 4.93it/s] 98%|█████████▊| 39/40 [00:08<00:00, 4.92it/s] 100%|██████████| 40/40 [00:08<00:00, 4.93it/s] 100%|██████████| 40/40 [00:08<00:00, 4.61it/s]Prediction
lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08Input
- seed
- 31512
- width
- 1024
- height
- 1024
- prompt
- a photo of TOK
- scheduler
- DPMSolverMultistep
- lora_scale
- 0.6
- num_outputs
- 1
- lora_weights
- https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar
- guidance_scale
- 7
- apply_watermark
- negative_prompt
- (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth
- prompt_strength
- 0.8
- num_inference_steps
- 40
{ "seed": 31512, "width": 1024, "height": 1024, "prompt": "a photo of TOK", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "lora_weights": "https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar", "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", { input: { seed: 31512, width: 1024, height: 1024, prompt: "a photo of TOK", scheduler: "DPMSolverMultistep", lora_scale: 0.6, num_outputs: 1, lora_weights: "https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar", guidance_scale: 7, apply_watermark: true, negative_prompt: "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", prompt_strength: 0.8, num_inference_steps: 40 } } ); // 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 lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", input={ "seed": 31512, "width": 1024, "height": 1024, "prompt": "a photo of TOK", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "lora_weights": "https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar", "guidance_scale": 7, "apply_watermark": True, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/realvisxl-v2.0 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": "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", "input": { "seed": 31512, "width": 1024, "height": 1024, "prompt": "a photo of TOK", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "lora_weights": "https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar", "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-09T14:56:13.487974Z", "created_at": "2023-11-09T14:55:59.674106Z", "data_removed": false, "error": null, "id": "ois7rttbxahlbfrwibetr36d2i", "input": { "seed": 31512, "width": 1024, "height": 1024, "prompt": "a photo of TOK", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "lora_weights": "https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar", "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 }, "logs": "Using seed: 31512\nEnsuring enough disk space...\nFree disk space: 1998425075712\nDownloading weights: https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar\nb'Downloaded 186 MB bytes in 0.555s (335 MB/s)\\nExtracted 186 MB in 0.072s (2.6 GB/s)\\n'\nDownloaded weights in 0.7540035247802734 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a photo of <s0><s1>\ntxt2img mode\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:10, 3.71it/s]\n 5%|▌ | 2/40 [00:00<00:10, 3.70it/s]\n 8%|▊ | 3/40 [00:00<00:10, 3.69it/s]\n 10%|█ | 4/40 [00:01<00:09, 3.68it/s]\n 12%|█▎ | 5/40 [00:01<00:09, 3.68it/s]\n 15%|█▌ | 6/40 [00:01<00:09, 3.68it/s]\n 18%|█▊ | 7/40 [00:01<00:08, 3.68it/s]\n 20%|██ | 8/40 [00:02<00:08, 3.68it/s]\n 22%|██▎ | 9/40 [00:02<00:08, 3.68it/s]\n 25%|██▌ | 10/40 [00:02<00:08, 3.68it/s]\n 28%|██▊ | 11/40 [00:02<00:07, 3.68it/s]\n 30%|███ | 12/40 [00:03<00:07, 3.68it/s]\n 32%|███▎ | 13/40 [00:03<00:07, 3.69it/s]\n 35%|███▌ | 14/40 [00:03<00:07, 3.69it/s]\n 38%|███▊ | 15/40 [00:04<00:06, 3.69it/s]\n 40%|████ | 16/40 [00:04<00:06, 3.69it/s]\n 42%|████▎ | 17/40 [00:04<00:06, 3.70it/s]\n 45%|████▌ | 18/40 [00:04<00:05, 3.70it/s]\n 48%|████▊ | 19/40 [00:05<00:05, 3.69it/s]\n 50%|█████ | 20/40 [00:05<00:05, 3.69it/s]\n 52%|█████▎ | 21/40 [00:05<00:05, 3.70it/s]\n 55%|█████▌ | 22/40 [00:05<00:04, 3.70it/s]\n 57%|█████▊ | 23/40 [00:06<00:04, 3.70it/s]\n 60%|██████ | 24/40 [00:06<00:04, 3.69it/s]\n 62%|██████▎ | 25/40 [00:06<00:04, 3.69it/s]\n 65%|██████▌ | 26/40 [00:07<00:03, 3.69it/s]\n 68%|██████▊ | 27/40 [00:07<00:03, 3.69it/s]\n 70%|███████ | 28/40 [00:07<00:03, 3.69it/s]\n 72%|███████▎ | 29/40 [00:07<00:02, 3.69it/s]\n 75%|███████▌ | 30/40 [00:08<00:02, 3.69it/s]\n 78%|███████▊ | 31/40 [00:08<00:02, 3.69it/s]\n 80%|████████ | 32/40 [00:08<00:02, 3.69it/s]\n 82%|████████▎ | 33/40 [00:08<00:01, 3.69it/s]\n 85%|████████▌ | 34/40 [00:09<00:01, 3.69it/s]\n 88%|████████▊ | 35/40 [00:09<00:01, 3.69it/s]\n 90%|█████████ | 36/40 [00:09<00:01, 3.69it/s]\n 92%|█████████▎| 37/40 [00:10<00:00, 3.69it/s]\n 95%|█████████▌| 38/40 [00:10<00:00, 3.69it/s]\n 98%|█████████▊| 39/40 [00:10<00:00, 3.69it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.69it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.69it/s]", "metrics": { "predict_time": 13.868404, "total_time": 13.813868 }, "output": [ "https://replicate.delivery/pbxt/L1mPgUU8OPa0EZXHeNnDfrInLTaePMm0DfffggyGTd5SDlqdE/out-0.png" ], "started_at": "2023-11-09T14:55:59.619570Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ois7rttbxahlbfrwibetr36d2i", "cancel": "https://api.replicate.com/v1/predictions/ois7rttbxahlbfrwibetr36d2i/cancel" }, "version": "7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08" }Generated inUsing seed: 31512 Ensuring enough disk space... Free disk space: 1998425075712 Downloading weights: https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar b'Downloaded 186 MB bytes in 0.555s (335 MB/s)\nExtracted 186 MB in 0.072s (2.6 GB/s)\n' Downloaded weights in 0.7540035247802734 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a photo of <s0><s1> txt2img mode 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:10, 3.71it/s] 5%|▌ | 2/40 [00:00<00:10, 3.70it/s] 8%|▊ | 3/40 [00:00<00:10, 3.69it/s] 10%|█ | 4/40 [00:01<00:09, 3.68it/s] 12%|█▎ | 5/40 [00:01<00:09, 3.68it/s] 15%|█▌ | 6/40 [00:01<00:09, 3.68it/s] 18%|█▊ | 7/40 [00:01<00:08, 3.68it/s] 20%|██ | 8/40 [00:02<00:08, 3.68it/s] 22%|██▎ | 9/40 [00:02<00:08, 3.68it/s] 25%|██▌ | 10/40 [00:02<00:08, 3.68it/s] 28%|██▊ | 11/40 [00:02<00:07, 3.68it/s] 30%|███ | 12/40 [00:03<00:07, 3.68it/s] 32%|███▎ | 13/40 [00:03<00:07, 3.69it/s] 35%|███▌ | 14/40 [00:03<00:07, 3.69it/s] 38%|███▊ | 15/40 [00:04<00:06, 3.69it/s] 40%|████ | 16/40 [00:04<00:06, 3.69it/s] 42%|████▎ | 17/40 [00:04<00:06, 3.70it/s] 45%|████▌ | 18/40 [00:04<00:05, 3.70it/s] 48%|████▊ | 19/40 [00:05<00:05, 3.69it/s] 50%|█████ | 20/40 [00:05<00:05, 3.69it/s] 52%|█████▎ | 21/40 [00:05<00:05, 3.70it/s] 55%|█████▌ | 22/40 [00:05<00:04, 3.70it/s] 57%|█████▊ | 23/40 [00:06<00:04, 3.70it/s] 60%|██████ | 24/40 [00:06<00:04, 3.69it/s] 62%|██████▎ | 25/40 [00:06<00:04, 3.69it/s] 65%|██████▌ | 26/40 [00:07<00:03, 3.69it/s] 68%|██████▊ | 27/40 [00:07<00:03, 3.69it/s] 70%|███████ | 28/40 [00:07<00:03, 3.69it/s] 72%|███████▎ | 29/40 [00:07<00:02, 3.69it/s] 75%|███████▌ | 30/40 [00:08<00:02, 3.69it/s] 78%|███████▊ | 31/40 [00:08<00:02, 3.69it/s] 80%|████████ | 32/40 [00:08<00:02, 3.69it/s] 82%|████████▎ | 33/40 [00:08<00:01, 3.69it/s] 85%|████████▌ | 34/40 [00:09<00:01, 3.69it/s] 88%|████████▊ | 35/40 [00:09<00:01, 3.69it/s] 90%|█████████ | 36/40 [00:09<00:01, 3.69it/s] 92%|█████████▎| 37/40 [00:10<00:00, 3.69it/s] 95%|█████████▌| 38/40 [00:10<00:00, 3.69it/s] 98%|█████████▊| 39/40 [00:10<00:00, 3.69it/s] 100%|██████████| 40/40 [00:10<00:00, 3.69it/s] 100%|██████████| 40/40 [00:10<00:00, 3.69it/s]Prediction
lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08ID57wsxtdbzimj4g32hetxjcvirmStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- seed
- 64811
- image
- width
- 1024
- height
- 1024
- prompt
- a latina woman with a pearl earring
- scheduler
- DPMSolverMultistep
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7
- apply_watermark
- negative_prompt
- (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth
- prompt_strength
- 0.8
- num_inference_steps
- 40
{ "seed": 64811, "image": "https://replicate.delivery/pbxt/Js49PGWMjU21D9Bg4U6uI7dX4p6UnA31W23TEQMO6Fnq3lKP/pearl1024.jpg", "width": 1024, "height": 1024, "prompt": "a latina woman with a pearl earring", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", { input: { seed: 64811, image: "https://replicate.delivery/pbxt/Js49PGWMjU21D9Bg4U6uI7dX4p6UnA31W23TEQMO6Fnq3lKP/pearl1024.jpg", width: 1024, height: 1024, prompt: "a latina woman with a pearl earring", scheduler: "DPMSolverMultistep", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7, apply_watermark: true, negative_prompt: "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", prompt_strength: 0.8, num_inference_steps: 40 } } ); // 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 lucataco/realvisxl-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", input={ "seed": 64811, "image": "https://replicate.delivery/pbxt/Js49PGWMjU21D9Bg4U6uI7dX4p6UnA31W23TEQMO6Fnq3lKP/pearl1024.jpg", "width": 1024, "height": 1024, "prompt": "a latina woman with a pearl earring", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7, "apply_watermark": True, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/realvisxl-v2.0 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": "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08", "input": { "seed": 64811, "image": "https://replicate.delivery/pbxt/Js49PGWMjU21D9Bg4U6uI7dX4p6UnA31W23TEQMO6Fnq3lKP/pearl1024.jpg", "width": 1024, "height": 1024, "prompt": "a latina woman with a pearl earring", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-13T17:48:34.925116Z", "created_at": "2023-11-13T17:48:23.774585Z", "data_removed": false, "error": null, "id": "57wsxtdbzimj4g32hetxjcvirm", "input": { "seed": 64811, "image": "https://replicate.delivery/pbxt/Js49PGWMjU21D9Bg4U6uI7dX4p6UnA31W23TEQMO6Fnq3lKP/pearl1024.jpg", "width": 1024, "height": 1024, "prompt": "a latina woman with a pearl earring", "scheduler": "DPMSolverMultistep", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7, "apply_watermark": true, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "prompt_strength": 0.8, "num_inference_steps": 40 }, "logs": "Using seed: 64811\nPrompt: a latina woman with a pearl earring\nimg2img mode\n 0%| | 0/32 [00:00<?, ?it/s]\n 3%|▎ | 1/32 [00:00<00:08, 3.67it/s]\n 6%|▋ | 2/32 [00:00<00:08, 3.66it/s]\n 9%|▉ | 3/32 [00:00<00:07, 3.65it/s]\n 12%|█▎ | 4/32 [00:01<00:07, 3.64it/s]\n 16%|█▌ | 5/32 [00:01<00:07, 3.64it/s]\n 19%|█▉ | 6/32 [00:01<00:07, 3.64it/s]\n 22%|██▏ | 7/32 [00:01<00:06, 3.64it/s]\n 25%|██▌ | 8/32 [00:02<00:06, 3.64it/s]\n 28%|██▊ | 9/32 [00:02<00:06, 3.64it/s]\n 31%|███▏ | 10/32 [00:02<00:06, 3.64it/s]\n 34%|███▍ | 11/32 [00:03<00:05, 3.64it/s]\n 38%|███▊ | 12/32 [00:03<00:05, 3.64it/s]\n 41%|████ | 13/32 [00:03<00:05, 3.64it/s]\n 44%|████▍ | 14/32 [00:03<00:04, 3.64it/s]\n 47%|████▋ | 15/32 [00:04<00:04, 3.64it/s]\n 50%|█████ | 16/32 [00:04<00:04, 3.64it/s]\n 53%|█████▎ | 17/32 [00:04<00:04, 3.64it/s]\n 56%|█████▋ | 18/32 [00:04<00:03, 3.64it/s]\n 59%|█████▉ | 19/32 [00:05<00:03, 3.64it/s]\n 62%|██████▎ | 20/32 [00:05<00:03, 3.64it/s]\n 66%|██████▌ | 21/32 [00:05<00:03, 3.63it/s]\n 69%|██████▉ | 22/32 [00:06<00:02, 3.63it/s]\n 72%|███████▏ | 23/32 [00:06<00:02, 3.63it/s]\n 75%|███████▌ | 24/32 [00:06<00:02, 3.63it/s]\n 78%|███████▊ | 25/32 [00:06<00:01, 3.63it/s]\n 81%|████████▏ | 26/32 [00:07<00:01, 3.63it/s]\n 84%|████████▍ | 27/32 [00:07<00:01, 3.63it/s]\n 88%|████████▊ | 28/32 [00:07<00:01, 3.63it/s]\n 91%|█████████ | 29/32 [00:07<00:00, 3.63it/s]\n 94%|█████████▍| 30/32 [00:08<00:00, 3.63it/s]\n 97%|█████████▋| 31/32 [00:08<00:00, 3.63it/s]\n100%|██████████| 32/32 [00:08<00:00, 3.63it/s]\n100%|██████████| 32/32 [00:08<00:00, 3.64it/s]", "metrics": { "predict_time": 11.159731, "total_time": 11.150531 }, "output": [ "https://replicate.delivery/pbxt/6D4sVhRfyVVpfk5o8xbKkhkWrvnGpfCsVBeJaQdZWryJ3EgHB/out-0.png" ], "started_at": "2023-11-13T17:48:23.765385Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/57wsxtdbzimj4g32hetxjcvirm", "cancel": "https://api.replicate.com/v1/predictions/57wsxtdbzimj4g32hetxjcvirm/cancel" }, "version": "7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08" }Generated inUsing seed: 64811 Prompt: a latina woman with a pearl earring img2img mode 0%| | 0/32 [00:00<?, ?it/s] 3%|▎ | 1/32 [00:00<00:08, 3.67it/s] 6%|▋ | 2/32 [00:00<00:08, 3.66it/s] 9%|▉ | 3/32 [00:00<00:07, 3.65it/s] 12%|█▎ | 4/32 [00:01<00:07, 3.64it/s] 16%|█▌ | 5/32 [00:01<00:07, 3.64it/s] 19%|█▉ | 6/32 [00:01<00:07, 3.64it/s] 22%|██▏ | 7/32 [00:01<00:06, 3.64it/s] 25%|██▌ | 8/32 [00:02<00:06, 3.64it/s] 28%|██▊ | 9/32 [00:02<00:06, 3.64it/s] 31%|███▏ | 10/32 [00:02<00:06, 3.64it/s] 34%|███▍ | 11/32 [00:03<00:05, 3.64it/s] 38%|███▊ | 12/32 [00:03<00:05, 3.64it/s] 41%|████ | 13/32 [00:03<00:05, 3.64it/s] 44%|████▍ | 14/32 [00:03<00:04, 3.64it/s] 47%|████▋ | 15/32 [00:04<00:04, 3.64it/s] 50%|█████ | 16/32 [00:04<00:04, 3.64it/s] 53%|█████▎ | 17/32 [00:04<00:04, 3.64it/s] 56%|█████▋ | 18/32 [00:04<00:03, 3.64it/s] 59%|█████▉ | 19/32 [00:05<00:03, 3.64it/s] 62%|██████▎ | 20/32 [00:05<00:03, 3.64it/s] 66%|██████▌ | 21/32 [00:05<00:03, 3.63it/s] 69%|██████▉ | 22/32 [00:06<00:02, 3.63it/s] 72%|███████▏ | 23/32 [00:06<00:02, 3.63it/s] 75%|███████▌ | 24/32 [00:06<00:02, 3.63it/s] 78%|███████▊ | 25/32 [00:06<00:01, 3.63it/s] 81%|████████▏ | 26/32 [00:07<00:01, 3.63it/s] 84%|████████▍ | 27/32 [00:07<00:01, 3.63it/s] 88%|████████▊ | 28/32 [00:07<00:01, 3.63it/s] 91%|█████████ | 29/32 [00:07<00:00, 3.63it/s] 94%|█████████▍| 30/32 [00:08<00:00, 3.63it/s] 97%|█████████▋| 31/32 [00:08<00:00, 3.63it/s] 100%|██████████| 32/32 [00:08<00:00, 3.63it/s] 100%|██████████| 32/32 [00:08<00:00, 3.64it/s]
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