brettimus / sdxl-lua
- Public
- 197 runs
-
L40S
Prediction
brettimus/sdxl-lua:05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1IDaqedi3dbtjr2ux3ojdrlhjpgk4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a cute TOK dog, in the style of Alphonse Mucha, art nouveau
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.74
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.94
- negative_prompt
- human, frame
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "a cute TOK dog, in the style of Alphonse Mucha, art nouveau", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.74, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.94, "negative_prompt": "human, frame", "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import 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 brettimus/sdxl-lua using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "brettimus/sdxl-lua:05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1", { input: { width: 1024, height: 1024, prompt: "a cute TOK dog, in the style of Alphonse Mucha, art nouveau", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.74, num_outputs: 4, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.94, negative_prompt: "human, frame", prompt_strength: 0.8, num_inference_steps: 50 } } ); // 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 replicate
Import the client:import replicate
Run brettimus/sdxl-lua using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "brettimus/sdxl-lua:05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1", input={ "width": 1024, "height": 1024, "prompt": "a cute TOK dog, in the style of Alphonse Mucha, art nouveau", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.74, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.94, "negative_prompt": "human, frame", "prompt_strength": 0.8, "num_inference_steps": 50 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run brettimus/sdxl-lua 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": "brettimus/sdxl-lua:05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1", "input": { "width": 1024, "height": 1024, "prompt": "a cute TOK dog, in the style of Alphonse Mucha, art nouveau", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.74, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.94, "negative_prompt": "human, frame", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-22T10:29:15.311331Z", "created_at": "2023-08-22T10:28:20.845045Z", "data_removed": false, "error": null, "id": "aqedi3dbtjr2ux3ojdrlhjpgk4", "input": { "width": 1024, "height": 1024, "prompt": "a cute TOK dog, in the style of Alphonse Mucha, art nouveau", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.74, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.94, "negative_prompt": "human, frame", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 38081\nPrompt: a cute <s0><s1> dog, in the style of Alphonse Mucha, art nouveau\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:45, 1.00it/s]\n 4%|▍ | 2/47 [00:01<00:44, 1.00it/s]\n 6%|▋ | 3/47 [00:02<00:43, 1.00it/s]\n 9%|▊ | 4/47 [00:03<00:42, 1.00it/s]\n 11%|█ | 5/47 [00:04<00:41, 1.00it/s]\n 13%|█▎ | 6/47 [00:05<00:40, 1.00it/s]\n 15%|█▍ | 7/47 [00:06<00:39, 1.00it/s]\n 17%|█▋ | 8/47 [00:07<00:38, 1.00it/s]\n 19%|█▉ | 9/47 [00:08<00:37, 1.00it/s]\n 21%|██▏ | 10/47 [00:09<00:36, 1.00it/s]\n 23%|██▎ | 11/47 [00:10<00:35, 1.00it/s]\n 26%|██▌ | 12/47 [00:11<00:34, 1.00it/s]\n 28%|██▊ | 13/47 [00:12<00:33, 1.00it/s]\n 30%|██▉ | 14/47 [00:13<00:32, 1.00it/s]\n 32%|███▏ | 15/47 [00:14<00:31, 1.00it/s]\n 34%|███▍ | 16/47 [00:15<00:30, 1.00it/s]\n 36%|███▌ | 17/47 [00:16<00:29, 1.00it/s]\n 38%|███▊ | 18/47 [00:17<00:28, 1.00it/s]\n 40%|████ | 19/47 [00:18<00:28, 1.00s/it]\n 43%|████▎ | 20/47 [00:19<00:27, 1.00s/it]\n 45%|████▍ | 21/47 [00:20<00:26, 1.00s/it]\n 47%|████▋ | 22/47 [00:21<00:25, 1.00s/it]\n 49%|████▉ | 23/47 [00:22<00:24, 1.00s/it]\n 51%|█████ | 24/47 [00:23<00:23, 1.00s/it]\n 53%|█████▎ | 25/47 [00:24<00:22, 1.00s/it]\n 55%|█████▌ | 26/47 [00:25<00:21, 1.00s/it]\n 57%|█████▋ | 27/47 [00:26<00:20, 1.00s/it]\n 60%|█████▉ | 28/47 [00:27<00:19, 1.00s/it]\n 62%|██████▏ | 29/47 [00:28<00:18, 1.00s/it]\n 64%|██████▍ | 30/47 [00:30<00:17, 1.00s/it]\n 66%|██████▌ | 31/47 [00:31<00:16, 1.00s/it]\n 68%|██████▊ | 32/47 [00:32<00:15, 1.00s/it]\n 70%|███████ | 33/47 [00:33<00:14, 1.00s/it]\n 72%|███████▏ | 34/47 [00:34<00:13, 1.00s/it]\n 74%|███████▍ | 35/47 [00:35<00:12, 1.00s/it]\n 77%|███████▋ | 36/47 [00:36<00:11, 1.00s/it]\n 79%|███████▊ | 37/47 [00:37<00:10, 1.01s/it]\n 81%|████████ | 38/47 [00:38<00:09, 1.00s/it]\n 83%|████████▎ | 39/47 [00:39<00:08, 1.00s/it]\n 85%|████████▌ | 40/47 [00:40<00:07, 1.00s/it]\n 87%|████████▋ | 41/47 [00:41<00:06, 1.00s/it]\n 89%|████████▉ | 42/47 [00:42<00:05, 1.00s/it]\n 91%|█████████▏| 43/47 [00:43<00:04, 1.00s/it]\n 94%|█████████▎| 44/47 [00:44<00:03, 1.00s/it]\n 96%|█████████▌| 45/47 [00:45<00:02, 1.00s/it]\n 98%|█████████▊| 46/47 [00:46<00:01, 1.00s/it]\n100%|██████████| 47/47 [00:47<00:00, 1.00s/it]\n100%|██████████| 47/47 [00:47<00:00, 1.00s/it]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:01, 1.23it/s]\n 67%|██████▋ | 2/3 [00:01<00:00, 1.23it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.23it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.23it/s]", "metrics": { "predict_time": 54.514519, "total_time": 54.466286 }, "output": [ "https://replicate.delivery/pbxt/v5ICtM9onTKgHZLZeAtfo6mVj7rfmriRh6BKpfHy68YlffIXE/out-0.png", "https://replicate.delivery/pbxt/yzelpwqocxVexEBezEsUOTzuKo69pfA75awERpGUqIurffIXE/out-1.png", "https://replicate.delivery/pbxt/cev0JbPPfJrKNUQCaENlnhze7QbxzBRRG1NYwCTFrpfoffIXE/out-2.png", "https://replicate.delivery/pbxt/WViLZFHGDcLcJdpgSEWCuqAHuKAuQNfZzsfaBLIpFwe2fPyFB/out-3.png" ], "started_at": "2023-08-22T10:28:20.796812Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/aqedi3dbtjr2ux3ojdrlhjpgk4", "cancel": "https://api.replicate.com/v1/predictions/aqedi3dbtjr2ux3ojdrlhjpgk4/cancel" }, "version": "05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1" }
Generated inUsing seed: 38081 Prompt: a cute <s0><s1> dog, in the style of Alphonse Mucha, art nouveau txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:45, 1.00it/s] 4%|▍ | 2/47 [00:01<00:44, 1.00it/s] 6%|▋ | 3/47 [00:02<00:43, 1.00it/s] 9%|▊ | 4/47 [00:03<00:42, 1.00it/s] 11%|█ | 5/47 [00:04<00:41, 1.00it/s] 13%|█▎ | 6/47 [00:05<00:40, 1.00it/s] 15%|█▍ | 7/47 [00:06<00:39, 1.00it/s] 17%|█▋ | 8/47 [00:07<00:38, 1.00it/s] 19%|█▉ | 9/47 [00:08<00:37, 1.00it/s] 21%|██▏ | 10/47 [00:09<00:36, 1.00it/s] 23%|██▎ | 11/47 [00:10<00:35, 1.00it/s] 26%|██▌ | 12/47 [00:11<00:34, 1.00it/s] 28%|██▊ | 13/47 [00:12<00:33, 1.00it/s] 30%|██▉ | 14/47 [00:13<00:32, 1.00it/s] 32%|███▏ | 15/47 [00:14<00:31, 1.00it/s] 34%|███▍ | 16/47 [00:15<00:30, 1.00it/s] 36%|███▌ | 17/47 [00:16<00:29, 1.00it/s] 38%|███▊ | 18/47 [00:17<00:28, 1.00it/s] 40%|████ | 19/47 [00:18<00:28, 1.00s/it] 43%|████▎ | 20/47 [00:19<00:27, 1.00s/it] 45%|████▍ | 21/47 [00:20<00:26, 1.00s/it] 47%|████▋ | 22/47 [00:21<00:25, 1.00s/it] 49%|████▉ | 23/47 [00:22<00:24, 1.00s/it] 51%|█████ | 24/47 [00:23<00:23, 1.00s/it] 53%|█████▎ | 25/47 [00:24<00:22, 1.00s/it] 55%|█████▌ | 26/47 [00:25<00:21, 1.00s/it] 57%|█████▋ | 27/47 [00:26<00:20, 1.00s/it] 60%|█████▉ | 28/47 [00:27<00:19, 1.00s/it] 62%|██████▏ | 29/47 [00:28<00:18, 1.00s/it] 64%|██████▍ | 30/47 [00:30<00:17, 1.00s/it] 66%|██████▌ | 31/47 [00:31<00:16, 1.00s/it] 68%|██████▊ | 32/47 [00:32<00:15, 1.00s/it] 70%|███████ | 33/47 [00:33<00:14, 1.00s/it] 72%|███████▏ | 34/47 [00:34<00:13, 1.00s/it] 74%|███████▍ | 35/47 [00:35<00:12, 1.00s/it] 77%|███████▋ | 36/47 [00:36<00:11, 1.00s/it] 79%|███████▊ | 37/47 [00:37<00:10, 1.01s/it] 81%|████████ | 38/47 [00:38<00:09, 1.00s/it] 83%|████████▎ | 39/47 [00:39<00:08, 1.00s/it] 85%|████████▌ | 40/47 [00:40<00:07, 1.00s/it] 87%|████████▋ | 41/47 [00:41<00:06, 1.00s/it] 89%|████████▉ | 42/47 [00:42<00:05, 1.00s/it] 91%|█████████▏| 43/47 [00:43<00:04, 1.00s/it] 94%|█████████▎| 44/47 [00:44<00:03, 1.00s/it] 96%|█████████▌| 45/47 [00:45<00:02, 1.00s/it] 98%|█████████▊| 46/47 [00:46<00:01, 1.00s/it] 100%|██████████| 47/47 [00:47<00:00, 1.00s/it] 100%|██████████| 47/47 [00:47<00:00, 1.00s/it] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:01, 1.23it/s] 67%|██████▋ | 2/3 [00:01<00:00, 1.23it/s] 100%|██████████| 3/3 [00:02<00:00, 1.23it/s] 100%|██████████| 3/3 [00:02<00:00, 1.23it/s]
Prediction
brettimus/sdxl-lua:05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1IDd4lsge3bvwrjvwkglwcilyfakqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a fantasy style portrait painting of a TOK dog in the style of francois boucher oil painting, rpg portrait
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.75
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.9
- negative_prompt
- human, frame
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "a fantasy style portrait painting of a TOK dog in the style of francois boucher oil painting, rpg portrait", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.75, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.9, "negative_prompt": "human, frame", "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import 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 brettimus/sdxl-lua using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "brettimus/sdxl-lua:05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1", { input: { width: 1024, height: 1024, prompt: "a fantasy style portrait painting of a TOK dog in the style of francois boucher oil painting, rpg portrait", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.75, num_outputs: 4, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.9, negative_prompt: "human, frame", prompt_strength: 0.8, num_inference_steps: 50 } } ); // 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 replicate
Import the client:import replicate
Run brettimus/sdxl-lua using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "brettimus/sdxl-lua:05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1", input={ "width": 1024, "height": 1024, "prompt": "a fantasy style portrait painting of a TOK dog in the style of francois boucher oil painting, rpg portrait", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.75, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.9, "negative_prompt": "human, frame", "prompt_strength": 0.8, "num_inference_steps": 50 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run brettimus/sdxl-lua 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": "brettimus/sdxl-lua:05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1", "input": { "width": 1024, "height": 1024, "prompt": "a fantasy style portrait painting of a TOK dog in the style of francois boucher oil painting, rpg portrait", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.75, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.9, "negative_prompt": "human, frame", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-30T14:37:43.213156Z", "created_at": "2023-08-30T14:36:46.811313Z", "data_removed": false, "error": null, "id": "d4lsge3bvwrjvwkglwcilyfakq", "input": { "width": 1024, "height": 1024, "prompt": "a fantasy style portrait painting of a TOK dog in the style of francois boucher oil painting, rpg portrait", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.75, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.9, "negative_prompt": "human, frame", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 18602\nPrompt: a fantasy style portrait painting of a <s0><s1> dog in the style of francois boucher oil painting, rpg portrait\ntxt2img mode\n 0%| | 0/45 [00:00<?, ?it/s]\n 2%|▏ | 1/45 [00:01<00:44, 1.01s/it]\n 4%|▍ | 2/45 [00:02<00:43, 1.01s/it]\n 7%|▋ | 3/45 [00:03<00:42, 1.01s/it]\n 9%|▉ | 4/45 [00:04<00:41, 1.01s/it]\n 11%|█ | 5/45 [00:05<00:40, 1.01s/it]\n 13%|█▎ | 6/45 [00:06<00:39, 1.00s/it]\n 16%|█▌ | 7/45 [00:07<00:38, 1.01s/it]\n 18%|█▊ | 8/45 [00:08<00:37, 1.01s/it]\n 20%|██ | 9/45 [00:09<00:36, 1.01s/it]\n 22%|██▏ | 10/45 [00:10<00:35, 1.01s/it]\n 24%|██▍ | 11/45 [00:11<00:34, 1.01s/it]\n 27%|██▋ | 12/45 [00:12<00:33, 1.01s/it]\n 29%|██▉ | 13/45 [00:13<00:32, 1.01s/it]\n 31%|███ | 14/45 [00:14<00:31, 1.01s/it]\n 33%|███▎ | 15/45 [00:15<00:30, 1.01s/it]\n 36%|███▌ | 16/45 [00:16<00:29, 1.01s/it]\n 38%|███▊ | 17/45 [00:17<00:28, 1.01s/it]\n 40%|████ | 18/45 [00:18<00:27, 1.01s/it]\n 42%|████▏ | 19/45 [00:19<00:26, 1.01s/it]\n 44%|████▍ | 20/45 [00:20<00:25, 1.01s/it]\n 47%|████▋ | 21/45 [00:21<00:24, 1.01s/it]\n 49%|████▉ | 22/45 [00:22<00:23, 1.01s/it]\n 51%|█████ | 23/45 [00:23<00:22, 1.01s/it]\n 53%|█████▎ | 24/45 [00:24<00:21, 1.01s/it]\n 56%|█████▌ | 25/45 [00:25<00:20, 1.01s/it]\n 58%|█████▊ | 26/45 [00:26<00:19, 1.01s/it]\n 60%|██████ | 27/45 [00:27<00:18, 1.01s/it]\n 62%|██████▏ | 28/45 [00:28<00:17, 1.01s/it]\n 64%|██████▍ | 29/45 [00:29<00:16, 1.01s/it]\n 67%|██████▋ | 30/45 [00:30<00:15, 1.01s/it]\n 69%|██████▉ | 31/45 [00:31<00:14, 1.01s/it]\n 71%|███████ | 32/45 [00:32<00:13, 1.01s/it]\n 73%|███████▎ | 33/45 [00:33<00:12, 1.01s/it]\n 76%|███████▌ | 34/45 [00:34<00:11, 1.01s/it]\n 78%|███████▊ | 35/45 [00:35<00:10, 1.01s/it]\n 80%|████████ | 36/45 [00:36<00:09, 1.01s/it]\n 82%|████████▏ | 37/45 [00:37<00:08, 1.01s/it]\n 84%|████████▍ | 38/45 [00:38<00:07, 1.01s/it]\n 87%|████████▋ | 39/45 [00:39<00:06, 1.01s/it]\n 89%|████████▉ | 40/45 [00:40<00:05, 1.01s/it]\n 91%|█████████ | 41/45 [00:41<00:04, 1.01s/it]\n 93%|█████████▎| 42/45 [00:42<00:03, 1.01s/it]\n 96%|█████████▌| 43/45 [00:43<00:02, 1.01s/it]\n 98%|█████████▊| 44/45 [00:44<00:01, 1.01s/it]\n100%|██████████| 45/45 [00:45<00:00, 1.01s/it]\n100%|██████████| 45/45 [00:45<00:00, 1.01s/it]\n 0%| | 0/5 [00:00<?, ?it/s]\n 20%|██ | 1/5 [00:00<00:03, 1.22it/s]\n 40%|████ | 2/5 [00:01<00:02, 1.22it/s]\n 60%|██████ | 3/5 [00:02<00:01, 1.22it/s]\n 80%|████████ | 4/5 [00:03<00:00, 1.21it/s]\n100%|██████████| 5/5 [00:04<00:00, 1.21it/s]\n100%|██████████| 5/5 [00:04<00:00, 1.22it/s]", "metrics": { "predict_time": 56.402415, "total_time": 56.401843 }, "output": [ "https://replicate.delivery/pbxt/OVBxRdSqPL65J9BXRtuNhH0T70DH3sw1cNcxSeyxZ9HaMovIA/out-0.png", "https://replicate.delivery/pbxt/7tI04eURrczlRqCWHBdBfcr8ZnBEs2D4zfut4EOyWo9qxgeFB/out-1.png", "https://replicate.delivery/pbxt/7s7JeVtazBSMaiYnojIMh5MyZLJDfLYskXnIbAzPUFI2YQfiA/out-2.png", "https://replicate.delivery/pbxt/CrUF1sd26F5ZGNF3iupPfphrQpN9V48fI2IA02hstvt2YQfiA/out-3.png" ], "started_at": "2023-08-30T14:36:46.810741Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/d4lsge3bvwrjvwkglwcilyfakq", "cancel": "https://api.replicate.com/v1/predictions/d4lsge3bvwrjvwkglwcilyfakq/cancel" }, "version": "05cffaa0b47ae12547e3cabcb19a56935fd551af4fa673abda40643a3e2e58e1" }
Generated inUsing seed: 18602 Prompt: a fantasy style portrait painting of a <s0><s1> dog in the style of francois boucher oil painting, rpg portrait txt2img mode 0%| | 0/45 [00:00<?, ?it/s] 2%|▏ | 1/45 [00:01<00:44, 1.01s/it] 4%|▍ | 2/45 [00:02<00:43, 1.01s/it] 7%|▋ | 3/45 [00:03<00:42, 1.01s/it] 9%|▉ | 4/45 [00:04<00:41, 1.01s/it] 11%|█ | 5/45 [00:05<00:40, 1.01s/it] 13%|█▎ | 6/45 [00:06<00:39, 1.00s/it] 16%|█▌ | 7/45 [00:07<00:38, 1.01s/it] 18%|█▊ | 8/45 [00:08<00:37, 1.01s/it] 20%|██ | 9/45 [00:09<00:36, 1.01s/it] 22%|██▏ | 10/45 [00:10<00:35, 1.01s/it] 24%|██▍ | 11/45 [00:11<00:34, 1.01s/it] 27%|██▋ | 12/45 [00:12<00:33, 1.01s/it] 29%|██▉ | 13/45 [00:13<00:32, 1.01s/it] 31%|███ | 14/45 [00:14<00:31, 1.01s/it] 33%|███▎ | 15/45 [00:15<00:30, 1.01s/it] 36%|███▌ | 16/45 [00:16<00:29, 1.01s/it] 38%|███▊ | 17/45 [00:17<00:28, 1.01s/it] 40%|████ | 18/45 [00:18<00:27, 1.01s/it] 42%|████▏ | 19/45 [00:19<00:26, 1.01s/it] 44%|████▍ | 20/45 [00:20<00:25, 1.01s/it] 47%|████▋ | 21/45 [00:21<00:24, 1.01s/it] 49%|████▉ | 22/45 [00:22<00:23, 1.01s/it] 51%|█████ | 23/45 [00:23<00:22, 1.01s/it] 53%|█████▎ | 24/45 [00:24<00:21, 1.01s/it] 56%|█████▌ | 25/45 [00:25<00:20, 1.01s/it] 58%|█████▊ | 26/45 [00:26<00:19, 1.01s/it] 60%|██████ | 27/45 [00:27<00:18, 1.01s/it] 62%|██████▏ | 28/45 [00:28<00:17, 1.01s/it] 64%|██████▍ | 29/45 [00:29<00:16, 1.01s/it] 67%|██████▋ | 30/45 [00:30<00:15, 1.01s/it] 69%|██████▉ | 31/45 [00:31<00:14, 1.01s/it] 71%|███████ | 32/45 [00:32<00:13, 1.01s/it] 73%|███████▎ | 33/45 [00:33<00:12, 1.01s/it] 76%|███████▌ | 34/45 [00:34<00:11, 1.01s/it] 78%|███████▊ | 35/45 [00:35<00:10, 1.01s/it] 80%|████████ | 36/45 [00:36<00:09, 1.01s/it] 82%|████████▏ | 37/45 [00:37<00:08, 1.01s/it] 84%|████████▍ | 38/45 [00:38<00:07, 1.01s/it] 87%|████████▋ | 39/45 [00:39<00:06, 1.01s/it] 89%|████████▉ | 40/45 [00:40<00:05, 1.01s/it] 91%|█████████ | 41/45 [00:41<00:04, 1.01s/it] 93%|█████████▎| 42/45 [00:42<00:03, 1.01s/it] 96%|█████████▌| 43/45 [00:43<00:02, 1.01s/it] 98%|█████████▊| 44/45 [00:44<00:01, 1.01s/it] 100%|██████████| 45/45 [00:45<00:00, 1.01s/it] 100%|██████████| 45/45 [00:45<00:00, 1.01s/it] 0%| | 0/5 [00:00<?, ?it/s] 20%|██ | 1/5 [00:00<00:03, 1.22it/s] 40%|████ | 2/5 [00:01<00:02, 1.22it/s] 60%|██████ | 3/5 [00:02<00:01, 1.22it/s] 80%|████████ | 4/5 [00:03<00:00, 1.21it/s] 100%|██████████| 5/5 [00:04<00:00, 1.21it/s] 100%|██████████| 5/5 [00:04<00:00, 1.22it/s]
Want to make some of these yourself?
Run this model