marcusschwarze / paul-mittelrheintaler
a public experiment with the AI generated figure of Paul Mittelrheintaler, a cool YouTuber in the middle Rhine Valley. Created by Marcus Schwarze
Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDbyc5zcn9a1rm00chhzctye93p4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Paul smiling into the camera, wearing a shirt, with Most Natural skin
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Paul smiling into the camera, wearing a shirt, with Most Natural skin ", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T18:02:00.055275Z", "created_at": "2024-08-26T18:01:32.240000Z", "data_removed": false, "error": null, "id": "byc5zcn9a1rm00chhzctye93p4", "input": { "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 25496\nPrompt: Paul smiling into the camera, wearing a shirt, with Most Natural skin\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 9.44s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.67it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.69it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.69it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]", "metrics": { "predict_time": 17.481377589, "total_time": 27.815275 }, "output": [ "https://replicate.delivery/yhqm/jNH0dIBYLXpuOtkMyeNpvYrKbfChogo8LMp7vOA5hFKXUnWTA/out-0.jpg" ], "started_at": "2024-08-26T18:01:42.573897Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/byc5zcn9a1rm00chhzctye93p4", "cancel": "https://api.replicate.com/v1/predictions/byc5zcn9a1rm00chhzctye93p4/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 25496 Prompt: Paul smiling into the camera, wearing a shirt, with Most Natural skin txt2img mode Using dev model Loaded LoRAs in 9.44s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s] 50%|█████ | 14/28 [00:03<00:03, 3.69it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.69it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDy1pnhc97ysrm60chhzdv6h51wgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard.
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T18:03:27.538758Z", "created_at": "2024-08-26T18:03:10.198000Z", "data_removed": false, "error": null, "id": "y1pnhc97ysrm60chhzdv6h51wg", "input": { "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 5749\nPrompt: Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard.\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 9.36s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.73it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.28it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.00it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.88it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.72it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.72it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.71it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.71it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.74it/s]", "metrics": { "predict_time": 17.330635999, "total_time": 17.340758 }, "output": [ "https://replicate.delivery/yhqm/S6Xe7lReUxuOPUPhuIHdWV46iWRs5TlVFirXIf2OP74eWdaNB/out-0.jpg" ], "started_at": "2024-08-26T18:03:10.208122Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/y1pnhc97ysrm60chhzdv6h51wg", "cancel": "https://api.replicate.com/v1/predictions/y1pnhc97ysrm60chhzdv6h51wg/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 5749 Prompt: Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. txt2img mode Using dev model Loaded LoRAs in 9.36s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.73it/s] 7%|▋ | 2/28 [00:00<00:06, 4.28it/s] 11%|█ | 3/28 [00:00<00:06, 4.00it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.88it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.72it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s] 50%|█████ | 14/28 [00:03<00:03, 3.72it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s] 61%|██████ | 17/28 [00:04<00:02, 3.71it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.71it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.74it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDy1pnhc97ysrm60chhzdv6h51wgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard.
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T18:03:27.538758Z", "created_at": "2024-08-26T18:03:10.198000Z", "data_removed": false, "error": null, "id": "y1pnhc97ysrm60chhzdv6h51wg", "input": { "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. ", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 5749\nPrompt: Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard.\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 9.36s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.73it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.28it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.00it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.88it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.72it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.72it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.71it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.71it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.74it/s]", "metrics": { "predict_time": 17.330635999, "total_time": 17.340758 }, "output": [ "https://replicate.delivery/yhqm/S6Xe7lReUxuOPUPhuIHdWV46iWRs5TlVFirXIf2OP74eWdaNB/out-0.jpg" ], "started_at": "2024-08-26T18:03:10.208122Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/y1pnhc97ysrm60chhzdv6h51wg", "cancel": "https://api.replicate.com/v1/predictions/y1pnhc97ysrm60chhzdv6h51wg/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 5749 Prompt: Paul smiling into the camera, wearing a shirt, with Most Natural skin. He shaves his beard. txt2img mode Using dev model Loaded LoRAs in 9.36s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.73it/s] 7%|▋ | 2/28 [00:00<00:06, 4.28it/s] 11%|█ | 3/28 [00:00<00:06, 4.00it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.88it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.72it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s] 50%|█████ | 14/28 [00:03<00:03, 3.72it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s] 61%|██████ | 17/28 [00:04<00:02, 3.71it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.71it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.74it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDxhcagva531rm60chhy1vehd204StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:27:26.128667Z", "created_at": "2024-08-26T16:27:10.488000Z", "data_removed": false, "error": null, "id": "xhcagva531rm60chhy1vehd204", "input": { "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 40250\nPrompt: Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 7.55s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.68it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]", "metrics": { "predict_time": 15.631152569, "total_time": 15.640667 }, "output": [ "https://replicate.delivery/yhqm/UeStA2Y7o320NiAYJtkWxdwwLxgGh3p7Af8gzLdHCpvt7lWTA/out-0.jpg" ], "started_at": "2024-08-26T16:27:10.497515Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xhcagva531rm60chhy1vehd204", "cancel": "https://api.replicate.com/v1/predictions/xhcagva531rm60chhy1vehd204/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 40250 Prompt: Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal txt2img mode Using dev model Loaded LoRAs in 7.55s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.68it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDhdydc0e5wsrm00chhxys5mfhvgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:21:33.419241Z", "created_at": "2024-08-26T16:21:10.246000Z", "data_removed": false, "error": null, "id": "hdydc0e5wsrm00chhxys5mfhvg", "input": { "model": "dev", "width": 1440, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 51435\nPrompt: Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim\ntxt2img mode\nUsing dev model\nfree=9711165808640\nDownloading weights\n2024-08-26T16:21:14Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpf58hgelg/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\n2024-08-26T16:21:16Z | INFO | [ Complete ] dest=/tmp/tmpf58hgelg/weights size=\"172 MB\" total_elapsed=1.466s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\nDownloaded weights in 1.50s\nLoaded LoRAs in 10.82s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.67it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.67it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.67it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]", "metrics": { "predict_time": 18.892943137, "total_time": 23.173241 }, "output": [ "https://replicate.delivery/yhqm/ppoHaQwQoe0KVqlXjhu5JMHVO0A6iE94RrfIko2GZjGN2lWTA/out-0.jpg" ], "started_at": "2024-08-26T16:21:14.526298Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hdydc0e5wsrm00chhxys5mfhvg", "cancel": "https://api.replicate.com/v1/predictions/hdydc0e5wsrm00chhxys5mfhvg/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 51435 Prompt: Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim txt2img mode Using dev model free=9711165808640 Downloading weights 2024-08-26T16:21:14Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpf58hgelg/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar 2024-08-26T16:21:16Z | INFO | [ Complete ] dest=/tmp/tmpf58hgelg/weights size="172 MB" total_elapsed=1.466s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar Downloaded weights in 1.50s Loaded LoRAs in 10.82s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s] 50%|█████ | 14/28 [00:03<00:03, 3.67it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s] 61%|██████ | 17/28 [00:04<00:02, 3.67it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDm74ftr7vt1rm00chhxy9zv0ermStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1366
- prompt
- Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1366, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1366, prompt: "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1366, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1366, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:20:33.432661Z", "created_at": "2024-08-26T16:20:18.512000Z", "data_removed": false, "error": null, "id": "m74ftr7vt1rm00chhxy9zv0erm", "input": { "model": "dev", "width": 1366, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 6491\nPrompt: Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 6.90s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.98it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.70it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.69it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 14.908871126, "total_time": 14.920661 }, "output": [ "https://replicate.delivery/yhqm/4afZLe5rEahoepxjxHSzQ1ccTfMAe7kbRUSa2MpeAeeFR1lWTA/out-0.jpg" ], "started_at": "2024-08-26T16:20:18.523790Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/m74ftr7vt1rm00chhxy9zv0erm", "cancel": "https://api.replicate.com/v1/predictions/m74ftr7vt1rm00chhxy9zv0erm/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 6491 Prompt: Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley txt2img mode Using dev model Loaded LoRAs in 6.90s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.98it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s] 50%|█████ | 14/28 [00:03<00:03, 3.70it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.69it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638ID1sg445kxj1rm40chhxxap3g2jcStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", prompt: "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:17:57.969333Z", "created_at": "2024-08-26T16:17:35.120000Z", "data_removed": false, "error": null, "id": "1sg445kxj1rm40chhxxap3g2jc", "input": { "model": "dev", "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 64051\nPrompt: Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley\ntxt2img mode\nUsing dev model\nfree=9252393639936\nDownloading weights\n2024-08-26T16:17:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpvh7u8k0h/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\n2024-08-26T16:17:41Z | INFO | [ Complete ] dest=/tmp/tmpvh7u8k0h/weights size=\"172 MB\" total_elapsed=1.504s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\nDownloaded weights in 1.53s\nLoaded LoRAs in 10.50s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.70it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.70it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]", "metrics": { "predict_time": 18.553647995, "total_time": 22.849333 }, "output": [ "https://replicate.delivery/yhqm/qhW2vFbFXPLHMBye5tIAgX4dkMHIwGMnRneZxRqdMPL1ylWTA/out-0.jpg" ], "started_at": "2024-08-26T16:17:39.415685Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/1sg445kxj1rm40chhxxap3g2jc", "cancel": "https://api.replicate.com/v1/predictions/1sg445kxj1rm40chhxxap3g2jc/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 64051 Prompt: Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley txt2img mode Using dev model free=9252393639936 Downloading weights 2024-08-26T16:17:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpvh7u8k0h/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar 2024-08-26T16:17:41Z | INFO | [ Complete ] dest=/tmp/tmpvh7u8k0h/weights size="172 MB" total_elapsed=1.504s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar Downloaded weights in 1.53s Loaded LoRAs in 10.50s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.70it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.70it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s]Prediction
marcusschwarze/paul-mittelrheintaler:995e0b3ede54fd1a5a9ea10cbd9c4759712988557ae7afbcd13d8fdeed2c55efIDj78tk0njghrm60chh81sxj505cStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Paul smiles charmingly in front of Deutsches Eck, in the middle rhine valley
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Paul smiles charmingly in front of Deutsches Eck, in the middle rhine valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:995e0b3ede54fd1a5a9ea10cbd9c4759712988557ae7afbcd13d8fdeed2c55ef", { input: { model: "dev", prompt: "Paul smiles charmingly in front of Deutsches Eck, in the middle rhine valley", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:995e0b3ede54fd1a5a9ea10cbd9c4759712988557ae7afbcd13d8fdeed2c55ef", input={ "model": "dev", "prompt": "Paul smiles charmingly in front of Deutsches Eck, in the middle rhine valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:995e0b3ede54fd1a5a9ea10cbd9c4759712988557ae7afbcd13d8fdeed2c55ef", "input": { "model": "dev", "prompt": "Paul smiles charmingly in front of Deutsches Eck, in the middle rhine valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-25T14:50:33.621198Z", "created_at": "2024-08-25T14:49:43.812000Z", "data_removed": false, "error": null, "id": "j78tk0njghrm60chh81sxj505c", "input": { "model": "dev", "prompt": "Paul smiles charmingly in front of Deutsches Eck, in the middle rhine valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "num_inference_steps": 28 }, "logs": "Using seed: 33248\nPrompt: Paul smiles charmingly in front of Deutsches Eck, in the middle rhine valley\ntxt2img mode\nUsing dev model\nfree=9529170317312\nDownloading weights\n2024-08-25T14:50:13Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpzzmmuu9p/weights url=https://replicate.delivery/yhqm/5iew6ftePPRN6oAgreiV6tuiSkbOfd5veaoe7JOicidKI5pqJA/trained_model.tar\n2024-08-25T14:50:18Z | INFO | [ Complete ] dest=/tmp/tmpzzmmuu9p/weights size=\"172 MB\" total_elapsed=5.106s url=https://replicate.delivery/yhqm/5iew6ftePPRN6oAgreiV6tuiSkbOfd5veaoe7JOicidKI5pqJA/trained_model.tar\nDownloaded weights in 5.13s\nLoaded LoRAs in 12.64s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.70it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.99it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.88it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.75it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.73it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.72it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.72it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.72it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.72it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.72it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.72it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.72it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.72it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.72it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.72it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.72it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.74it/s]", "metrics": { "predict_time": 20.623024307, "total_time": 49.809198 }, "output": [ "https://replicate.delivery/yhqm/mfRHk722yV1eFkekDO4AcnxJnN3zPC5Zx9EfAWJsGqQnr9YNB/out-0.jpg" ], "started_at": "2024-08-25T14:50:12.998174Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/j78tk0njghrm60chh81sxj505c", "cancel": "https://api.replicate.com/v1/predictions/j78tk0njghrm60chh81sxj505c/cancel" }, "version": "995e0b3ede54fd1a5a9ea10cbd9c4759712988557ae7afbcd13d8fdeed2c55ef" }Generated inUsing seed: 33248 Prompt: Paul smiles charmingly in front of Deutsches Eck, in the middle rhine valley txt2img mode Using dev model free=9529170317312 Downloading weights 2024-08-25T14:50:13Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpzzmmuu9p/weights url=https://replicate.delivery/yhqm/5iew6ftePPRN6oAgreiV6tuiSkbOfd5veaoe7JOicidKI5pqJA/trained_model.tar 2024-08-25T14:50:18Z | INFO | [ Complete ] dest=/tmp/tmpzzmmuu9p/weights size="172 MB" total_elapsed=5.106s url=https://replicate.delivery/yhqm/5iew6ftePPRN6oAgreiV6tuiSkbOfd5veaoe7JOicidKI5pqJA/trained_model.tar Downloaded weights in 5.13s Loaded LoRAs in 12.64s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.70it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 3.99it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.88it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.75it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.73it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.72it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s] 50%|█████ | 14/28 [00:03<00:03, 3.72it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.72it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.72it/s] 61%|██████ | 17/28 [00:04<00:02, 3.72it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.72it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.72it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.72it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.72it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.72it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.72it/s] 100%|██████████| 28/28 [00:07<00:00, 3.74it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638ID2bvgxt1p4xrm60chn3ssjrbdcgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Paul playing beach volley ball during Olympics in the middle rhine valley
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Paul playing beach volley ball during Olympics in the middle rhine valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Paul playing beach volley ball during Olympics in the middle rhine valley", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Paul playing beach volley ball during Olympics in the middle rhine valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Paul playing beach volley ball during Olympics in the middle rhine valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-31T15:00:18.608992Z", "created_at": "2024-08-31T14:59:57.095000Z", "data_removed": false, "error": null, "id": "2bvgxt1p4xrm60chn3ssjrbdcg", "input": { "model": "dev", "width": 1440, "prompt": "Paul playing beach volley ball during Olympics in the middle rhine valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 53111\nPrompt: Paul playing beach volley ball during Olympics in the middle rhine valley\ntxt2img mode\nUsing dev model\nfree=9501282553856\nDownloading weights\n2024-08-31T14:59:59Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpyahxbhvm/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\n2024-08-31T15:00:01Z | INFO | [ Complete ] dest=/tmp/tmpyahxbhvm/weights size=\"172 MB\" total_elapsed=1.832s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\nDownloaded weights in 1.86s\nLoaded LoRAs in 10.67s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.67it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.22it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]", "metrics": { "predict_time": 18.724017794, "total_time": 21.513992 }, "output": [ "https://replicate.delivery/yhqm/De6Vp3xMe8oedJMBNSXyLAQ4nEMzM801ySpLJjhbrrMFQcwmA/out-0.jpg" ], "started_at": "2024-08-31T14:59:59.884974Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/2bvgxt1p4xrm60chn3ssjrbdcg", "cancel": "https://api.replicate.com/v1/predictions/2bvgxt1p4xrm60chn3ssjrbdcg/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 53111 Prompt: Paul playing beach volley ball during Olympics in the middle rhine valley txt2img mode Using dev model free=9501282553856 Downloading weights 2024-08-31T14:59:59Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpyahxbhvm/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar 2024-08-31T15:00:01Z | INFO | [ Complete ] dest=/tmp/tmpyahxbhvm/weights size="172 MB" total_elapsed=1.832s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar Downloaded weights in 1.86s Loaded LoRAs in 10.67s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.22it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDm74ftr7vt1rm00chhxy9zv0ermStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1366
- prompt
- Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1366, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1366, prompt: "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1366, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1366, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:20:33.432661Z", "created_at": "2024-08-26T16:20:18.512000Z", "data_removed": false, "error": null, "id": "m74ftr7vt1rm00chhxy9zv0erm", "input": { "model": "dev", "width": 1366, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 6491\nPrompt: Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 6.90s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.98it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.70it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.69it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 14.908871126, "total_time": 14.920661 }, "output": [ "https://replicate.delivery/yhqm/4afZLe5rEahoepxjxHSzQ1ccTfMAe7kbRUSa2MpeAeeFR1lWTA/out-0.jpg" ], "started_at": "2024-08-26T16:20:18.523790Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/m74ftr7vt1rm00chhxy9zv0erm", "cancel": "https://api.replicate.com/v1/predictions/m74ftr7vt1rm00chhxy9zv0erm/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 6491 Prompt: Close-Update Portrait of Paul Mittelrheintaler. He surfs on a Wave in the Middle Rhine Valley txt2img mode Using dev model Loaded LoRAs in 6.90s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.98it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s] 50%|█████ | 14/28 [00:03<00:03, 3.70it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.69it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDhdydc0e5wsrm00chhxys5mfhvgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:21:33.419241Z", "created_at": "2024-08-26T16:21:10.246000Z", "data_removed": false, "error": null, "id": "hdydc0e5wsrm00chhxys5mfhvg", "input": { "model": "dev", "width": 1440, "prompt": "Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 51435\nPrompt: Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim\ntxt2img mode\nUsing dev model\nfree=9711165808640\nDownloading weights\n2024-08-26T16:21:14Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpf58hgelg/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\n2024-08-26T16:21:16Z | INFO | [ Complete ] dest=/tmp/tmpf58hgelg/weights size=\"172 MB\" total_elapsed=1.466s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\nDownloaded weights in 1.50s\nLoaded LoRAs in 10.82s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.67it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.67it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.67it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]", "metrics": { "predict_time": 18.892943137, "total_time": 23.173241 }, "output": [ "https://replicate.delivery/yhqm/ppoHaQwQoe0KVqlXjhu5JMHVO0A6iE94RrfIko2GZjGN2lWTA/out-0.jpg" ], "started_at": "2024-08-26T16:21:14.526298Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hdydc0e5wsrm00chhxys5mfhvg", "cancel": "https://api.replicate.com/v1/predictions/hdydc0e5wsrm00chhxys5mfhvg/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 51435 Prompt: Close-Update Portrait of Paul Mittelrheintaler. In Rüdesheim txt2img mode Using dev model free=9711165808640 Downloading weights 2024-08-26T16:21:14Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpf58hgelg/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar 2024-08-26T16:21:16Z | INFO | [ Complete ] dest=/tmp/tmpf58hgelg/weights size="172 MB" total_elapsed=1.466s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar Downloaded weights in 1.50s Loaded LoRAs in 10.82s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s] 50%|█████ | 14/28 [00:03<00:03, 3.67it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s] 61%|██████ | 17/28 [00:04<00:02, 3.67it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638ID8jgg0g5q5drm20chhxz9xg28q8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Close-Up Portrait of Paul Mittelrheintaler. In Rüdesheim
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Close-Up Portrait of Paul Mittelrheintaler. In Rüdesheim", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:22:46.053192Z", "created_at": "2024-08-26T16:22:12.011000Z", "data_removed": false, "error": null, "id": "8jgg0g5q5drm20chhxz9xg28q8", "input": { "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler. In Rüdesheim", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 12270\nPrompt: Close-Up Portrait of Paul Mittelrheintaler. In Rüdesheim\ntxt2img mode\nUsing dev model\nfree=9584344301568\nDownloading weights\n2024-08-26T16:22:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgb806t1x/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\n2024-08-26T16:22:20Z | INFO | [ Complete ] dest=/tmp/tmpgb806t1x/weights size=\"172 MB\" total_elapsed=1.428s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar\nDownloaded weights in 1.46s\nLoaded LoRAs in 19.06s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.71it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.98it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.72it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.72it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.71it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.72it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.72it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.71it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.72it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.74it/s]", "metrics": { "predict_time": 27.054439469, "total_time": 34.042192 }, "output": [ "https://replicate.delivery/yhqm/59HI4prG0HKqCF22B6ohOOiEcP2hwfMfFHik0tDBfgeWdXaNB/out-0.jpg" ], "started_at": "2024-08-26T16:22:18.998752Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/8jgg0g5q5drm20chhxz9xg28q8", "cancel": "https://api.replicate.com/v1/predictions/8jgg0g5q5drm20chhxz9xg28q8/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 12270 Prompt: Close-Up Portrait of Paul Mittelrheintaler. In Rüdesheim txt2img mode Using dev model free=9584344301568 Downloading weights 2024-08-26T16:22:19Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgb806t1x/weights url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar 2024-08-26T16:22:20Z | INFO | [ Complete ] dest=/tmp/tmpgb806t1x/weights size="172 MB" total_elapsed=1.428s url=https://replicate.delivery/yhqm/GFdiuIA7IUoDKBItlycNaRprnlniJSIkrfw8cFtT0ubP2SrJA/trained_model.tar Downloaded weights in 1.46s Loaded LoRAs in 19.06s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.71it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 3.98it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.72it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s] 50%|█████ | 14/28 [00:03<00:03, 3.72it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s] 61%|██████ | 17/28 [00:04<00:02, 3.71it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.72it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.71it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.72it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.71it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.72it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.74it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDp3165p22psrm00chhy1809vkh0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic.
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic.", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic.", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic.", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic.", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:26:21.553551Z", "created_at": "2024-08-26T16:26:04.342000Z", "data_removed": false, "error": null, "id": "p3165p22psrm00chhy1809vkh0", "input": { "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic.", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 62493\nPrompt: Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic.\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 9.23s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.72it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.28it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.01it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.89it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.75it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.73it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.73it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.72it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.72it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.72it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.72it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.72it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.72it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.72it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.72it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.72it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.72it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.75it/s]", "metrics": { "predict_time": 17.201848036, "total_time": 17.211551 }, "output": [ "https://replicate.delivery/yhqm/lf1Tfw63pQgk6EEFC4M681lS0cN08bJVny6MbnAMH4Rt6lWTA/out-0.jpg" ], "started_at": "2024-08-26T16:26:04.351703Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/p3165p22psrm00chhy1809vkh0", "cancel": "https://api.replicate.com/v1/predictions/p3165p22psrm00chhy1809vkh0/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 62493 Prompt: Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic. txt2img mode Using dev model Loaded LoRAs in 9.23s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.72it/s] 7%|▋ | 2/28 [00:00<00:06, 4.28it/s] 11%|█ | 3/28 [00:00<00:06, 4.01it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.89it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.76it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.75it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.74it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.73it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.73it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.73it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.72it/s] 50%|█████ | 14/28 [00:03<00:03, 3.72it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.72it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.72it/s] 61%|██████ | 17/28 [00:04<00:02, 3.72it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.72it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.72it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.72it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.72it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.72it/s] 100%|██████████| 28/28 [00:07<00:00, 3.72it/s] 100%|██████████| 28/28 [00:07<00:00, 3.75it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDxhcagva531rm60chhy1vehd204StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:27:26.128667Z", "created_at": "2024-08-26T16:27:10.488000Z", "data_removed": false, "error": null, "id": "xhcagva531rm60chhy1vehd204", "input": { "model": "dev", "width": 1440, "prompt": "Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 40250\nPrompt: Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 7.55s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.68it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]", "metrics": { "predict_time": 15.631152569, "total_time": 15.640667 }, "output": [ "https://replicate.delivery/yhqm/UeStA2Y7o320NiAYJtkWxdwwLxgGh3p7Af8gzLdHCpvt7lWTA/out-0.jpg" ], "started_at": "2024-08-26T16:27:10.497515Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xhcagva531rm60chhy1vehd204", "cancel": "https://api.replicate.com/v1/predictions/xhcagva531rm60chhy1vehd204/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 40250 Prompt: Close-Up Portrait of Paul Mittelrheintaler with normal Skin, extreme realistic, in Front of Niederwalddenkmal txt2img mode Using dev model Loaded LoRAs in 7.55s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.68it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638ID10khzbjds5rm20chhy68yc4a84StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Paul drinking a Glas of white vine on a boat
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Paul drinking a Glas of white vine on a boat", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Paul drinking a Glas of white vine on a boat", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Paul drinking a Glas of white vine on a boat", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Paul drinking a Glas of white vine on a boat", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T16:37:19.442760Z", "created_at": "2024-08-26T16:37:02.537000Z", "data_removed": false, "error": null, "id": "10khzbjds5rm20chhy68yc4a84", "input": { "model": "dev", "width": 1440, "prompt": "Paul drinking a Glas of white vine on a boat", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 5543\nPrompt: Paul drinking a Glas of white vine on a boat\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 7.90s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.68it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.23it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]", "metrics": { "predict_time": 15.934767472, "total_time": 16.90576 }, "output": [ "https://replicate.delivery/yhqm/ifwG6FkCewliLUK20ms9qgMONadEvoEo9fpB1wYZUT9eTYaNB/out-0.jpg" ], "started_at": "2024-08-26T16:37:03.507992Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/10khzbjds5rm20chhy68yc4a84", "cancel": "https://api.replicate.com/v1/predictions/10khzbjds5rm20chhy68yc4a84/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 5543 Prompt: Paul drinking a Glas of white vine on a boat txt2img mode Using dev model Loaded LoRAs in 7.90s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.68it/s] 7%|▋ | 2/28 [00:00<00:06, 4.23it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.68it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.68it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638IDhpxg5pe6qhrm00chhyh9p0rcxmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Paul drinking a Glas of white vine on a boat
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Paul drinking a Glas of white vine on a boat", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Paul drinking a Glas of white vine on a boat", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Paul drinking a Glas of white vine on a boat", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Paul drinking a Glas of white vine on a boat", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T17:01:59.961108Z", "created_at": "2024-08-26T17:01:35.292000Z", "data_removed": false, "error": null, "id": "hpxg5pe6qhrm00chhyh9p0rcxm", "input": { "model": "dev", "width": 1440, "prompt": "Paul drinking a Glas of white vine on a boat", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 30470\nPrompt: Paul drinking a Glas of white vine on a boat\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 8.96s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.70it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.27it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.98it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.72it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.71it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.70it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 16.955610437, "total_time": 24.669108 }, "output": [ "https://replicate.delivery/yhqm/O5rxuvTdpg6VGFloFNgn9976IsZAcaGUp5cfLyYZkNjDOTrJA/out-0.jpg" ], "started_at": "2024-08-26T17:01:43.005498Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hpxg5pe6qhrm00chhyh9p0rcxm", "cancel": "https://api.replicate.com/v1/predictions/hpxg5pe6qhrm00chhyh9p0rcxm/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 30470 Prompt: Paul drinking a Glas of white vine on a boat txt2img mode Using dev model Loaded LoRAs in 8.96s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.70it/s] 7%|▋ | 2/28 [00:00<00:06, 4.27it/s] 11%|█ | 3/28 [00:00<00:06, 3.98it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.77it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.72it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s] 50%|█████ | 14/28 [00:03<00:03, 3.71it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.70it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.71it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]Prediction
marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638ID81xc0474gxrm40chhyj9frtvcrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 1440
- prompt
- Paul smiling into the camera, wearing a shirt
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", { input: { model: "dev", width: 1440, prompt: "Paul smiling into the camera, wearing a shirt", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "jpg", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); // 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 marcusschwarze/paul-mittelrheintaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", input={ "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run marcusschwarze/paul-mittelrheintaler 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": "marcusschwarze/paul-mittelrheintaler:eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638", "input": { "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-26T17:04:11.492751Z", "created_at": "2024-08-26T17:03:53.991000Z", "data_removed": false, "error": null, "id": "81xc0474gxrm40chhyj9frtvcr", "input": { "model": "dev", "width": 1440, "prompt": "Paul smiling into the camera, wearing a shirt", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 18757\nPrompt: Paul smiling into the camera, wearing a shirt\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 9.48s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.71it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.28it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.00it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.88it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.75it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.73it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.72it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.71it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.71it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.74it/s]", "metrics": { "predict_time": 17.491250046, "total_time": 17.501751 }, "output": [ "https://replicate.delivery/yhqm/VZJgyfIqGXRILytkiSxlZVGbAmuEL2axP1Yrs5oZHEkFPTrJA/out-0.jpg" ], "started_at": "2024-08-26T17:03:54.001501Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/81xc0474gxrm40chhyj9frtvcr", "cancel": "https://api.replicate.com/v1/predictions/81xc0474gxrm40chhyj9frtvcr/cancel" }, "version": "eab40b1ee63ea98986caf4123e21931075d0d4fc753c98ebff2f0d566bd7c638" }Generated inUsing seed: 18757 Prompt: Paul smiling into the camera, wearing a shirt txt2img mode Using dev model Loaded LoRAs in 9.48s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.71it/s] 7%|▋ | 2/28 [00:00<00:06, 4.28it/s] 11%|█ | 3/28 [00:00<00:06, 4.00it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.88it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.82it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.75it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.73it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.72it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s] 50%|█████ | 14/28 [00:03<00:03, 3.71it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s] 61%|██████ | 17/28 [00:04<00:02, 3.71it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.71it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.71it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.71it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.70it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.74it/s]
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