melgor
/
stabledesign_interiordesign
Transfer empty room into fabulous interior design
Prediction
melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0IDz6b9q5dww5rgp0cg4sj91cnv1rStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 35853
- prompt
- A glamorous master bedroom in Hollywood Regency style, boasting a plush tufted headboard, mirrored furniture reflecting elegance, luxurious fabrics in rich textures, and opulent gold accents for a touch of luxury.
- img_size
- 640
- strength
- 0.9
- num_steps
- 50
- image_base
- guidance_scale
- 10
{ "seed": 35853, "prompt": "A glamorous master bedroom in Hollywood Regency style, boasting a plush tufted headboard, mirrored furniture reflecting elegance, luxurious fabrics in rich textures, and opulent gold accents for a touch of luxury.", "img_size": 640, "strength": 0.9, "num_steps": 50, "image_base": "https://replicate.delivery/pbxt/L71nWgMUQvH7zKHG3U9YYdfREv1ybOfO1Q5ntak3YmUJizSR/image_0.jpg", "guidance_scale": 10 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run melgor/stabledesign_interiordesign using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0", { input: { seed: 35853, prompt: "A glamorous master bedroom in Hollywood Regency style, boasting a plush tufted headboard, mirrored furniture reflecting elegance, luxurious fabrics in rich textures, and opulent gold accents for a touch of luxury.", img_size: 640, strength: 0.9, num_steps: 50, image_base: "https://replicate.delivery/pbxt/L71nWgMUQvH7zKHG3U9YYdfREv1ybOfO1Q5ntak3YmUJizSR/image_0.jpg", guidance_scale: 10 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun melgor/stabledesign_interiordesign using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0", input={ "seed": 35853, "prompt": "A glamorous master bedroom in Hollywood Regency style, boasting a plush tufted headboard, mirrored furniture reflecting elegance, luxurious fabrics in rich textures, and opulent gold accents for a touch of luxury.", "img_size": 640, "strength": 0.9, "num_steps": 50, "image_base": "https://replicate.delivery/pbxt/L71nWgMUQvH7zKHG3U9YYdfREv1ybOfO1Q5ntak3YmUJizSR/image_0.jpg", "guidance_scale": 10 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run melgor/stabledesign_interiordesign 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": "5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0", "input": { "seed": 35853, "prompt": "A glamorous master bedroom in Hollywood Regency style, boasting a plush tufted headboard, mirrored furniture reflecting elegance, luxurious fabrics in rich textures, and opulent gold accents for a touch of luxury.", "img_size": 640, "strength": 0.9, "num_steps": 50, "image_base": "https://replicate.delivery/pbxt/L71nWgMUQvH7zKHG3U9YYdfREv1ybOfO1Q5ntak3YmUJizSR/image_0.jpg", "guidance_scale": 10 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-06-17T13:37:22.508770Z", "created_at": "2024-06-17T13:30:54.561000Z", "data_removed": false, "error": null, "id": "z6b9q5dww5rgp0cg4sj91cnv1r", "input": { "seed": 35853, "prompt": "A glamorous master bedroom in Hollywood Regency style, boasting a plush tufted headboard, mirrored furniture reflecting elegance, luxurious fabrics in rich textures, and opulent gold accents for a touch of luxury.", "img_size": 640, "strength": 0.9, "num_steps": 50, "image_base": "https://replicate.delivery/pbxt/L71nWgMUQvH7zKHG3U9YYdfREv1ybOfO1Q5ntak3YmUJizSR/image_0.jpg", "guidance_scale": 10 }, "logs": "/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.)\nreturn F.conv2d(input, weight, bias, self.stride,\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.68it/s]\n 8%|▊ | 4/50 [00:00<00:02, 15.39it/s]\n 14%|█▍ | 7/50 [00:00<00:02, 18.52it/s]\n 20%|██ | 10/50 [00:00<00:02, 19.84it/s]\n 26%|██▌ | 13/50 [00:00<00:01, 20.74it/s]\n 32%|███▏ | 16/50 [00:00<00:01, 21.31it/s]\n 38%|███▊ | 19/50 [00:00<00:01, 21.66it/s]\n 44%|████▍ | 22/50 [00:01<00:01, 21.90it/s]\n 50%|█████ | 25/50 [00:01<00:01, 22.06it/s]\n 56%|█████▌ | 28/50 [00:01<00:00, 22.17it/s]\n 62%|██████▏ | 31/50 [00:01<00:00, 22.22it/s]\n 68%|██████▊ | 34/50 [00:01<00:00, 22.03it/s]\n 74%|███████▍ | 37/50 [00:01<00:00, 22.10it/s]\n 80%|████████ | 40/50 [00:01<00:00, 22.11it/s]\n 86%|████████▌ | 43/50 [00:02<00:00, 22.17it/s]\n 92%|█████████▏| 46/50 [00:02<00:00, 22.21it/s]\n 98%|█████████▊| 49/50 [00:02<00:00, 22.19it/s]\n100%|██████████| 50/50 [00:02<00:00, 21.25it/s]\n 0%| | 0/45 [00:00<?, ?it/s]\n 2%|▏ | 1/45 [00:00<00:07, 6.14it/s]\n 7%|▋ | 3/45 [00:00<00:04, 9.30it/s]\n 11%|█ | 5/45 [00:00<00:03, 10.74it/s]\n 16%|█▌ | 7/45 [00:00<00:03, 11.46it/s]\n 20%|██ | 9/45 [00:00<00:03, 11.86it/s]\n 24%|██▍ | 11/45 [00:00<00:02, 12.11it/s]\n 29%|██▉ | 13/45 [00:01<00:02, 12.25it/s]\n 33%|███▎ | 15/45 [00:01<00:02, 12.35it/s]\n 38%|███▊ | 17/45 [00:01<00:02, 12.42it/s]\n 42%|████▏ | 19/45 [00:01<00:02, 12.45it/s]\n 47%|████▋ | 21/45 [00:01<00:01, 12.48it/s]\n 51%|█████ | 23/45 [00:01<00:01, 12.50it/s]\n 56%|█████▌ | 25/45 [00:02<00:01, 12.52it/s]\n 60%|██████ | 27/45 [00:02<00:01, 12.54it/s]\n 64%|██████▍ | 29/45 [00:02<00:01, 12.55it/s]\n 69%|██████▉ | 31/45 [00:02<00:01, 12.56it/s]\n 73%|███████▎ | 33/45 [00:02<00:00, 12.56it/s]\n 78%|███████▊ | 35/45 [00:02<00:00, 12.57it/s]\n 82%|████████▏ | 37/45 [00:03<00:00, 12.58it/s]\n 87%|████████▋ | 39/45 [00:03<00:00, 12.57it/s]\n 91%|█████████ | 41/45 [00:03<00:00, 12.58it/s]\n 96%|█████████▌| 43/45 [00:03<00:00, 12.61it/s]\n100%|██████████| 45/45 [00:03<00:00, 12.62it/s]\n100%|██████████| 45/45 [00:03<00:00, 12.24it/s]", "metrics": { "predict_time": 11.483450089, "total_time": 387.94777 }, "output": "https://replicate.delivery/pbxt/xyCGKiWjs04hKRFZaGOfSqgTCsO1spe53eMr5OBbcenHh79LB/design.png", "started_at": "2024-06-17T13:37:11.025319Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/z6b9q5dww5rgp0cg4sj91cnv1r", "cancel": "https://api.replicate.com/v1/predictions/z6b9q5dww5rgp0cg4sj91cnv1r/cancel" }, "version": "5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0" }Generated in/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.) return F.conv2d(input, weight, bias, self.stride, 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.68it/s] 8%|▊ | 4/50 [00:00<00:02, 15.39it/s] 14%|█▍ | 7/50 [00:00<00:02, 18.52it/s] 20%|██ | 10/50 [00:00<00:02, 19.84it/s] 26%|██▌ | 13/50 [00:00<00:01, 20.74it/s] 32%|███▏ | 16/50 [00:00<00:01, 21.31it/s] 38%|███▊ | 19/50 [00:00<00:01, 21.66it/s] 44%|████▍ | 22/50 [00:01<00:01, 21.90it/s] 50%|█████ | 25/50 [00:01<00:01, 22.06it/s] 56%|█████▌ | 28/50 [00:01<00:00, 22.17it/s] 62%|██████▏ | 31/50 [00:01<00:00, 22.22it/s] 68%|██████▊ | 34/50 [00:01<00:00, 22.03it/s] 74%|███████▍ | 37/50 [00:01<00:00, 22.10it/s] 80%|████████ | 40/50 [00:01<00:00, 22.11it/s] 86%|████████▌ | 43/50 [00:02<00:00, 22.17it/s] 92%|█████████▏| 46/50 [00:02<00:00, 22.21it/s] 98%|█████████▊| 49/50 [00:02<00:00, 22.19it/s] 100%|██████████| 50/50 [00:02<00:00, 21.25it/s] 0%| | 0/45 [00:00<?, ?it/s] 2%|▏ | 1/45 [00:00<00:07, 6.14it/s] 7%|▋ | 3/45 [00:00<00:04, 9.30it/s] 11%|█ | 5/45 [00:00<00:03, 10.74it/s] 16%|█▌ | 7/45 [00:00<00:03, 11.46it/s] 20%|██ | 9/45 [00:00<00:03, 11.86it/s] 24%|██▍ | 11/45 [00:00<00:02, 12.11it/s] 29%|██▉ | 13/45 [00:01<00:02, 12.25it/s] 33%|███▎ | 15/45 [00:01<00:02, 12.35it/s] 38%|███▊ | 17/45 [00:01<00:02, 12.42it/s] 42%|████▏ | 19/45 [00:01<00:02, 12.45it/s] 47%|████▋ | 21/45 [00:01<00:01, 12.48it/s] 51%|█████ | 23/45 [00:01<00:01, 12.50it/s] 56%|█████▌ | 25/45 [00:02<00:01, 12.52it/s] 60%|██████ | 27/45 [00:02<00:01, 12.54it/s] 64%|██████▍ | 29/45 [00:02<00:01, 12.55it/s] 69%|██████▉ | 31/45 [00:02<00:01, 12.56it/s] 73%|███████▎ | 33/45 [00:02<00:00, 12.56it/s] 78%|███████▊ | 35/45 [00:02<00:00, 12.57it/s] 82%|████████▏ | 37/45 [00:03<00:00, 12.58it/s] 87%|████████▋ | 39/45 [00:03<00:00, 12.57it/s] 91%|█████████ | 41/45 [00:03<00:00, 12.58it/s] 96%|█████████▌| 43/45 [00:03<00:00, 12.61it/s] 100%|██████████| 45/45 [00:03<00:00, 12.62it/s] 100%|██████████| 45/45 [00:03<00:00, 12.24it/s]Prediction
melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0IDzh2fdba30nrgg0cg651adf8q2mStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 35853
- prompt
- A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.
- img_size
- 640
- strength
- 0.9
- num_steps
- 50
- image_base
- guidance_scale
- 10
{ "seed": 35853, "prompt": "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.", "img_size": 640, "strength": 0.9, "num_steps": 50, "image_base": "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp", "guidance_scale": 10 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run melgor/stabledesign_interiordesign using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0", { input: { seed: 35853, prompt: "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.", img_size: 640, strength: 0.9, num_steps: 50, image_base: "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp", guidance_scale: 10 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun melgor/stabledesign_interiordesign using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0", input={ "seed": 35853, "prompt": "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.", "img_size": 640, "strength": 0.9, "num_steps": 50, "image_base": "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp", "guidance_scale": 10 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run melgor/stabledesign_interiordesign 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": "5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0", "input": { "seed": 35853, "prompt": "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.", "img_size": 640, "strength": 0.9, "num_steps": 50, "image_base": "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp", "guidance_scale": 10 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-06-19T16:14:36.616606Z", "created_at": "2024-06-19T16:09:04.517000Z", "data_removed": false, "error": null, "id": "zh2fdba30nrgg0cg651adf8q2m", "input": { "seed": 35853, "prompt": "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.", "img_size": 640, "strength": 0.9, "num_steps": 50, "image_base": "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp", "guidance_scale": 10 }, "logs": "/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.)\nreturn F.conv2d(input, weight, bias, self.stride,\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.63it/s]\n 8%|▊ | 4/50 [00:00<00:02, 16.21it/s]\n 14%|█▍ | 7/50 [00:00<00:02, 19.46it/s]\n 20%|██ | 10/50 [00:00<00:01, 21.01it/s]\n 26%|██▌ | 13/50 [00:00<00:01, 22.16it/s]\n 32%|███▏ | 16/50 [00:00<00:01, 22.43it/s]\n 38%|███▊ | 19/50 [00:00<00:01, 22.43it/s]\n 44%|████▍ | 22/50 [00:01<00:01, 22.68it/s]\n 50%|█████ | 25/50 [00:01<00:01, 22.65it/s]\n 56%|█████▌ | 28/50 [00:01<00:00, 22.69it/s]\n 62%|██████▏ | 31/50 [00:01<00:00, 22.91it/s]\n 68%|██████▊ | 34/50 [00:01<00:00, 23.43it/s]\n 74%|███████▍ | 37/50 [00:01<00:00, 23.73it/s]\n 80%|████████ | 40/50 [00:01<00:00, 23.58it/s]\n 86%|████████▌ | 43/50 [00:01<00:00, 23.60it/s]\n 92%|█████████▏| 46/50 [00:02<00:00, 23.92it/s]\n 98%|█████████▊| 49/50 [00:02<00:00, 24.13it/s]\n100%|██████████| 50/50 [00:02<00:00, 22.49it/s]\n 0%| | 0/45 [00:00<?, ?it/s]\n 2%|▏ | 1/45 [00:00<00:06, 6.31it/s]\n 7%|▋ | 3/45 [00:00<00:04, 9.86it/s]\n 11%|█ | 5/45 [00:00<00:03, 11.58it/s]\n 16%|█▌ | 7/45 [00:00<00:03, 12.44it/s]\n 20%|██ | 9/45 [00:00<00:02, 12.92it/s]\n 24%|██▍ | 11/45 [00:00<00:02, 13.24it/s]\n 29%|██▉ | 13/45 [00:01<00:02, 13.43it/s]\n 33%|███▎ | 15/45 [00:01<00:02, 13.55it/s]\n 38%|███▊ | 17/45 [00:01<00:02, 13.61it/s]\n 42%|████▏ | 19/45 [00:01<00:01, 13.65it/s]\n 47%|████▋ | 21/45 [00:01<00:01, 13.68it/s]\n 51%|█████ | 23/45 [00:01<00:01, 13.71it/s]\n 56%|█████▌ | 25/45 [00:01<00:01, 13.74it/s]\n 60%|██████ | 27/45 [00:02<00:01, 13.77it/s]\n 64%|██████▍ | 29/45 [00:02<00:01, 13.77it/s]\n 69%|██████▉ | 31/45 [00:02<00:01, 13.73it/s]\n 73%|███████▎ | 33/45 [00:02<00:00, 13.74it/s]\n 78%|███████▊ | 35/45 [00:02<00:00, 13.74it/s]\n 82%|████████▏ | 37/45 [00:02<00:00, 13.70it/s]\n 87%|████████▋ | 39/45 [00:02<00:00, 13.53it/s]\n 91%|█████████ | 41/45 [00:03<00:00, 13.60it/s]\n 96%|█████████▌| 43/45 [00:03<00:00, 13.63it/s]\n100%|██████████| 45/45 [00:03<00:00, 13.67it/s]\n100%|██████████| 45/45 [00:03<00:00, 13.32it/s]", "metrics": { "predict_time": 9.495151756, "total_time": 332.099606 }, "output": "https://replicate.delivery/pbxt/HZHevsx6TEVFW6QINyzgNfSyrtwcIfknzOoGUDTR1bJYvWAmA/design.png", "started_at": "2024-06-19T16:14:27.121454Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zh2fdba30nrgg0cg651adf8q2m", "cancel": "https://api.replicate.com/v1/predictions/zh2fdba30nrgg0cg651adf8q2m/cancel" }, "version": "5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0" }Generated in/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.) return F.conv2d(input, weight, bias, self.stride, 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.63it/s] 8%|▊ | 4/50 [00:00<00:02, 16.21it/s] 14%|█▍ | 7/50 [00:00<00:02, 19.46it/s] 20%|██ | 10/50 [00:00<00:01, 21.01it/s] 26%|██▌ | 13/50 [00:00<00:01, 22.16it/s] 32%|███▏ | 16/50 [00:00<00:01, 22.43it/s] 38%|███▊ | 19/50 [00:00<00:01, 22.43it/s] 44%|████▍ | 22/50 [00:01<00:01, 22.68it/s] 50%|█████ | 25/50 [00:01<00:01, 22.65it/s] 56%|█████▌ | 28/50 [00:01<00:00, 22.69it/s] 62%|██████▏ | 31/50 [00:01<00:00, 22.91it/s] 68%|██████▊ | 34/50 [00:01<00:00, 23.43it/s] 74%|███████▍ | 37/50 [00:01<00:00, 23.73it/s] 80%|████████ | 40/50 [00:01<00:00, 23.58it/s] 86%|████████▌ | 43/50 [00:01<00:00, 23.60it/s] 92%|█████████▏| 46/50 [00:02<00:00, 23.92it/s] 98%|█████████▊| 49/50 [00:02<00:00, 24.13it/s] 100%|██████████| 50/50 [00:02<00:00, 22.49it/s] 0%| | 0/45 [00:00<?, ?it/s] 2%|▏ | 1/45 [00:00<00:06, 6.31it/s] 7%|▋ | 3/45 [00:00<00:04, 9.86it/s] 11%|█ | 5/45 [00:00<00:03, 11.58it/s] 16%|█▌ | 7/45 [00:00<00:03, 12.44it/s] 20%|██ | 9/45 [00:00<00:02, 12.92it/s] 24%|██▍ | 11/45 [00:00<00:02, 13.24it/s] 29%|██▉ | 13/45 [00:01<00:02, 13.43it/s] 33%|███▎ | 15/45 [00:01<00:02, 13.55it/s] 38%|███▊ | 17/45 [00:01<00:02, 13.61it/s] 42%|████▏ | 19/45 [00:01<00:01, 13.65it/s] 47%|████▋ | 21/45 [00:01<00:01, 13.68it/s] 51%|█████ | 23/45 [00:01<00:01, 13.71it/s] 56%|█████▌ | 25/45 [00:01<00:01, 13.74it/s] 60%|██████ | 27/45 [00:02<00:01, 13.77it/s] 64%|██████▍ | 29/45 [00:02<00:01, 13.77it/s] 69%|██████▉ | 31/45 [00:02<00:01, 13.73it/s] 73%|███████▎ | 33/45 [00:02<00:00, 13.74it/s] 78%|███████▊ | 35/45 [00:02<00:00, 13.74it/s] 82%|████████▏ | 37/45 [00:02<00:00, 13.70it/s] 87%|████████▋ | 39/45 [00:02<00:00, 13.53it/s] 91%|█████████ | 41/45 [00:03<00:00, 13.60it/s] 96%|█████████▌| 43/45 [00:03<00:00, 13.63it/s] 100%|██████████| 45/45 [00:03<00:00, 13.67it/s] 100%|██████████| 45/45 [00:03<00:00, 13.32it/s]
Want to make some of these yourself?
Run this model