brucecris
/
bruce1
The first Bruce model.
- Public
- 10 runs
-
H100
Prediction
brucecris/bruce1:1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719ID3kwbq897hnrm60chfzfvb2mm80StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- “Model” standing on a beach looking away from the camera.
- lora_scale
- 2
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- png
- guidance_scale
- 10
- output_quality
- 80
- num_inference_steps
- 50
{ "model": "dev", "prompt": "“Model” standing on a beach looking away from the camera. ", "lora_scale": 2, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 10, "output_quality": 80, "num_inference_steps": 50 }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 brucecris/bruce1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "brucecris/bruce1:1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719", { input: { model: "dev", prompt: "“Model” standing on a beach looking away from the camera. ", lora_scale: 2, num_outputs: 4, aspect_ratio: "1:1", output_format: "png", guidance_scale: 10, output_quality: 80, 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 replicateImport the client:import replicateRun brucecris/bruce1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "brucecris/bruce1:1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719", input={ "model": "dev", "prompt": "“Model” standing on a beach looking away from the camera. ", "lora_scale": 2, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 10, "output_quality": 80, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run brucecris/bruce1 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": "brucecris/bruce1:1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719", "input": { "model": "dev", "prompt": "“Model” standing on a beach looking away from the camera. ", "lora_scale": 2, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 10, "output_quality": 80, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-23T15:34:40.949382Z", "created_at": "2024-08-23T15:33:36.781000Z", "data_removed": false, "error": null, "id": "3kwbq897hnrm60chfzfvb2mm80", "input": { "model": "dev", "prompt": "“Model” standing on a beach looking away from the camera. ", "lora_scale": 2, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 10, "output_quality": 80, "num_inference_steps": 50 }, "logs": "Using seed: 57072\nPrompt: “Model” standing on a beach looking away from the camera.\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nLoRA weights loaded successfully\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:01<00:49, 1.02s/it]\n 4%|▍ | 2/50 [00:01<00:43, 1.11it/s]\n 6%|▌ | 3/50 [00:02<00:44, 1.05it/s]\n 8%|▊ | 4/50 [00:03<00:45, 1.02it/s]\n 10%|█ | 5/50 [00:04<00:44, 1.00it/s]\n 12%|█▏ | 6/50 [00:05<00:44, 1.00s/it]\n 14%|█▍ | 7/50 [00:06<00:43, 1.01s/it]\n 16%|█▌ | 8/50 [00:07<00:42, 1.01s/it]\n 18%|█▊ | 9/50 [00:08<00:41, 1.01s/it]\n 20%|██ | 10/50 [00:09<00:40, 1.01s/it]\n 22%|██▏ | 11/50 [00:11<00:39, 1.02s/it]\n 24%|██▍ | 12/50 [00:12<00:38, 1.02s/it]\n 26%|██▌ | 13/50 [00:13<00:37, 1.02s/it]\n 28%|██▊ | 14/50 [00:14<00:36, 1.02s/it]\n 30%|███ | 15/50 [00:15<00:35, 1.02s/it]\n 32%|███▏ | 16/50 [00:16<00:34, 1.02s/it]\n 34%|███▍ | 17/50 [00:17<00:33, 1.02s/it]\n 36%|███▌ | 18/50 [00:18<00:32, 1.02s/it]\n 38%|███▊ | 19/50 [00:19<00:31, 1.02s/it]\n 40%|████ | 20/50 [00:20<00:30, 1.02s/it]\n 42%|████▏ | 21/50 [00:21<00:29, 1.02s/it]\n 44%|████▍ | 22/50 [00:22<00:28, 1.02s/it]\n 46%|████▌ | 23/50 [00:23<00:27, 1.02s/it]\n 48%|████▊ | 24/50 [00:24<00:26, 1.02s/it]\n 50%|█████ | 25/50 [00:25<00:25, 1.02s/it]\n 52%|█████▏ | 26/50 [00:26<00:24, 1.02s/it]\n 54%|█████▍ | 27/50 [00:27<00:23, 1.02s/it]\n 56%|█████▌ | 28/50 [00:28<00:22, 1.02s/it]\n 58%|█████▊ | 29/50 [00:29<00:21, 1.02s/it]\n 60%|██████ | 30/50 [00:30<00:20, 1.02s/it]\n 62%|██████▏ | 31/50 [00:31<00:19, 1.02s/it]\n 64%|██████▍ | 32/50 [00:32<00:18, 1.02s/it]\n 66%|██████▌ | 33/50 [00:33<00:17, 1.02s/it]\n 68%|██████▊ | 34/50 [00:34<00:16, 1.02s/it]\n 70%|███████ | 35/50 [00:35<00:15, 1.02s/it]\n 72%|███████▏ | 36/50 [00:36<00:14, 1.02s/it]\n 74%|███████▍ | 37/50 [00:37<00:13, 1.02s/it]\n 76%|███████▌ | 38/50 [00:38<00:12, 1.02s/it]\n 78%|███████▊ | 39/50 [00:39<00:11, 1.02s/it]\n 80%|████████ | 40/50 [00:40<00:10, 1.02s/it]\n 82%|████████▏ | 41/50 [00:41<00:09, 1.02s/it]\n 84%|████████▍ | 42/50 [00:42<00:08, 1.02s/it]\n 86%|████████▌ | 43/50 [00:43<00:07, 1.02s/it]\n 88%|████████▊ | 44/50 [00:44<00:06, 1.02s/it]\n 90%|█████████ | 45/50 [00:45<00:05, 1.02s/it]\n 92%|█████████▏| 46/50 [00:46<00:04, 1.02s/it]\n 94%|█████████▍| 47/50 [00:47<00:03, 1.02s/it]\n 96%|█████████▌| 48/50 [00:48<00:02, 1.02s/it]\n 98%|█████████▊| 49/50 [00:49<00:01, 1.02s/it]\n100%|██████████| 50/50 [00:50<00:00, 1.02s/it]\n100%|██████████| 50/50 [00:50<00:00, 1.02s/it]\nPotential NSFW content was detected in one or more images. A black image will be returned instead. Try again with a different prompt and/or seed.\nNSFW content detected in image 2\nNSFW content detected in image 3", "metrics": { "predict_time": 61.578703878, "total_time": 64.168382 }, "output": [ "https://replicate.delivery/yhqm/tIVKNCOM4X6yFFCC3lLiyeHssYP8NUar0eqkKmDrGkLQ4lVTA/out-0.png", "https://replicate.delivery/yhqm/U3Hfy6H6iiT4diW89fAvO3Nf2uGxeeVgdTvUjiPxeCqJEeyqJA/out-1.png" ], "started_at": "2024-08-23T15:33:39.370678Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3kwbq897hnrm60chfzfvb2mm80", "cancel": "https://api.replicate.com/v1/predictions/3kwbq897hnrm60chfzfvb2mm80/cancel" }, "version": "1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719" }Generated inUsing seed: 57072 Prompt: “Model” standing on a beach looking away from the camera. txt2img mode Using dev model Loading LoRA weights LoRA weights loaded successfully 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<00:49, 1.02s/it] 4%|▍ | 2/50 [00:01<00:43, 1.11it/s] 6%|▌ | 3/50 [00:02<00:44, 1.05it/s] 8%|▊ | 4/50 [00:03<00:45, 1.02it/s] 10%|█ | 5/50 [00:04<00:44, 1.00it/s] 12%|█▏ | 6/50 [00:05<00:44, 1.00s/it] 14%|█▍ | 7/50 [00:06<00:43, 1.01s/it] 16%|█▌ | 8/50 [00:07<00:42, 1.01s/it] 18%|█▊ | 9/50 [00:08<00:41, 1.01s/it] 20%|██ | 10/50 [00:09<00:40, 1.01s/it] 22%|██▏ | 11/50 [00:11<00:39, 1.02s/it] 24%|██▍ | 12/50 [00:12<00:38, 1.02s/it] 26%|██▌ | 13/50 [00:13<00:37, 1.02s/it] 28%|██▊ | 14/50 [00:14<00:36, 1.02s/it] 30%|███ | 15/50 [00:15<00:35, 1.02s/it] 32%|███▏ | 16/50 [00:16<00:34, 1.02s/it] 34%|███▍ | 17/50 [00:17<00:33, 1.02s/it] 36%|███▌ | 18/50 [00:18<00:32, 1.02s/it] 38%|███▊ | 19/50 [00:19<00:31, 1.02s/it] 40%|████ | 20/50 [00:20<00:30, 1.02s/it] 42%|████▏ | 21/50 [00:21<00:29, 1.02s/it] 44%|████▍ | 22/50 [00:22<00:28, 1.02s/it] 46%|████▌ | 23/50 [00:23<00:27, 1.02s/it] 48%|████▊ | 24/50 [00:24<00:26, 1.02s/it] 50%|█████ | 25/50 [00:25<00:25, 1.02s/it] 52%|█████▏ | 26/50 [00:26<00:24, 1.02s/it] 54%|█████▍ | 27/50 [00:27<00:23, 1.02s/it] 56%|█████▌ | 28/50 [00:28<00:22, 1.02s/it] 58%|█████▊ | 29/50 [00:29<00:21, 1.02s/it] 60%|██████ | 30/50 [00:30<00:20, 1.02s/it] 62%|██████▏ | 31/50 [00:31<00:19, 1.02s/it] 64%|██████▍ | 32/50 [00:32<00:18, 1.02s/it] 66%|██████▌ | 33/50 [00:33<00:17, 1.02s/it] 68%|██████▊ | 34/50 [00:34<00:16, 1.02s/it] 70%|███████ | 35/50 [00:35<00:15, 1.02s/it] 72%|███████▏ | 36/50 [00:36<00:14, 1.02s/it] 74%|███████▍ | 37/50 [00:37<00:13, 1.02s/it] 76%|███████▌ | 38/50 [00:38<00:12, 1.02s/it] 78%|███████▊ | 39/50 [00:39<00:11, 1.02s/it] 80%|████████ | 40/50 [00:40<00:10, 1.02s/it] 82%|████████▏ | 41/50 [00:41<00:09, 1.02s/it] 84%|████████▍ | 42/50 [00:42<00:08, 1.02s/it] 86%|████████▌ | 43/50 [00:43<00:07, 1.02s/it] 88%|████████▊ | 44/50 [00:44<00:06, 1.02s/it] 90%|█████████ | 45/50 [00:45<00:05, 1.02s/it] 92%|█████████▏| 46/50 [00:46<00:04, 1.02s/it] 94%|█████████▍| 47/50 [00:47<00:03, 1.02s/it] 96%|█████████▌| 48/50 [00:48<00:02, 1.02s/it] 98%|█████████▊| 49/50 [00:49<00:01, 1.02s/it] 100%|██████████| 50/50 [00:50<00:00, 1.02s/it] 100%|██████████| 50/50 [00:50<00:00, 1.02s/it] Potential NSFW content was detected in one or more images. A black image will be returned instead. Try again with a different prompt and/or seed. NSFW content detected in image 2 NSFW content detected in image 3Prediction
brucecris/bruce1:1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719IDrj1ejxq6thrm40chfywa24exkgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Image of “model” standing in a stage speaking to an audience.
- lora_scale
- 1
- num_outputs
- 3
- aspect_ratio
- 1:1
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 40
{ "model": "dev", "prompt": "Image of “model” standing in a stage speaking to an audience. ", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 40 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run brucecris/bruce1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "brucecris/bruce1:1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719", { input: { model: "dev", prompt: "Image of “model” standing in a stage speaking to an audience. ", lora_scale: 1, num_outputs: 3, aspect_ratio: "1:1", output_format: "png", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 40 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun brucecris/bruce1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "brucecris/bruce1:1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719", input={ "model": "dev", "prompt": "Image of “model” standing in a stage speaking to an audience. ", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run brucecris/bruce1 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": "brucecris/bruce1:1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719", "input": { "model": "dev", "prompt": "Image of “model” standing in a stage speaking to an audience. ", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-23T14:52:32.306034Z", "created_at": "2024-08-23T14:51:49.844000Z", "data_removed": false, "error": null, "id": "rj1ejxq6thrm40chfywa24exkg", "input": { "model": "dev", "prompt": "Image of “model” standing in a stage speaking to an audience. ", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 40 }, "logs": "Using seed: 54679\nPrompt: Image of “model” standing in a stage speaking to an audience.\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9743398563840\nDownloading weights\n2024-08-23T14:51:49Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/0d1ee8f7bcebdf4f url=https://replicate.delivery/yhqm/d2PHCfyNb1zkWKCdVr96nzAdRXIiDvdlJsBmvOq3Ph1ztoqJA/trained_model.tar\n2024-08-23T14:51:51Z | INFO | [ Complete ] dest=/src/weights-cache/0d1ee8f7bcebdf4f size=\"172 MB\" total_elapsed=1.717s url=https://replicate.delivery/yhqm/d2PHCfyNb1zkWKCdVr96nzAdRXIiDvdlJsBmvOq3Ph1ztoqJA/trained_model.tar\nb''\nDownloaded weights in 1.749300241470337 seconds\nLoRA weights loaded successfully\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:29, 1.33it/s]\n 5%|▌ | 2/40 [00:01<00:24, 1.52it/s]\n 8%|▊ | 3/40 [00:02<00:25, 1.42it/s]\n 10%|█ | 4/40 [00:02<00:26, 1.38it/s]\n 12%|█▎ | 5/40 [00:03<00:25, 1.36it/s]\n 15%|█▌ | 6/40 [00:04<00:25, 1.35it/s]\n 18%|█▊ | 7/40 [00:05<00:24, 1.34it/s]\n 20%|██ | 8/40 [00:05<00:24, 1.33it/s]\n 22%|██▎ | 9/40 [00:06<00:23, 1.33it/s]\n 25%|██▌ | 10/40 [00:07<00:22, 1.32it/s]\n 28%|██▊ | 11/40 [00:08<00:21, 1.32it/s]\n 30%|███ | 12/40 [00:08<00:21, 1.32it/s]\n 32%|███▎ | 13/40 [00:09<00:20, 1.32it/s]\n 35%|███▌ | 14/40 [00:10<00:19, 1.32it/s]\n 38%|███▊ | 15/40 [00:11<00:18, 1.32it/s]\n 40%|████ | 16/40 [00:11<00:18, 1.32it/s]\n 42%|████▎ | 17/40 [00:12<00:17, 1.32it/s]\n 45%|████▌ | 18/40 [00:13<00:16, 1.32it/s]\n 48%|████▊ | 19/40 [00:14<00:15, 1.32it/s]\n 50%|█████ | 20/40 [00:14<00:15, 1.32it/s]\n 52%|█████▎ | 21/40 [00:15<00:14, 1.32it/s]\n 55%|█████▌ | 22/40 [00:16<00:13, 1.32it/s]\n 57%|█████▊ | 23/40 [00:17<00:12, 1.32it/s]\n 60%|██████ | 24/40 [00:18<00:12, 1.32it/s]\n 62%|██████▎ | 25/40 [00:18<00:11, 1.32it/s]\n 65%|██████▌ | 26/40 [00:19<00:10, 1.32it/s]\n 68%|██████▊ | 27/40 [00:20<00:09, 1.32it/s]\n 70%|███████ | 28/40 [00:21<00:09, 1.32it/s]\n 72%|███████▎ | 29/40 [00:21<00:08, 1.32it/s]\n 75%|███████▌ | 30/40 [00:22<00:07, 1.32it/s]\n 78%|███████▊ | 31/40 [00:23<00:06, 1.32it/s]\n 80%|████████ | 32/40 [00:24<00:06, 1.32it/s]\n 82%|████████▎ | 33/40 [00:24<00:05, 1.32it/s]\n 85%|████████▌ | 34/40 [00:25<00:04, 1.32it/s]\n 88%|████████▊ | 35/40 [00:26<00:03, 1.32it/s]\n 90%|█████████ | 36/40 [00:27<00:03, 1.32it/s]\n 92%|█████████▎| 37/40 [00:27<00:02, 1.32it/s]\n 95%|█████████▌| 38/40 [00:28<00:01, 1.32it/s]\n 98%|█████████▊| 39/40 [00:29<00:00, 1.32it/s]\n100%|██████████| 40/40 [00:30<00:00, 1.32it/s]\n100%|██████████| 40/40 [00:30<00:00, 1.33it/s]", "metrics": { "predict_time": 42.452469447, "total_time": 42.462034 }, "output": [ "https://replicate.delivery/yhqm/8KAxPHoJo0J5FxlHSMPLt4ZyiC1aETmEaItUYSfOO41XoyqJA/out-0.png", "https://replicate.delivery/yhqm/1ADxmjRIVEqtOlpZ9tDImrN4UTJr3M20IyoeYnROUtSYoyqJA/out-1.png", "https://replicate.delivery/yhqm/MnFb9HeZYRzJTKXIlReG4pDRwUZsK6LYcteuVvmmVgfBDVWNB/out-2.png" ], "started_at": "2024-08-23T14:51:49.853565Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rj1ejxq6thrm40chfywa24exkg", "cancel": "https://api.replicate.com/v1/predictions/rj1ejxq6thrm40chfywa24exkg/cancel" }, "version": "1e388f43f63564d517b0454152877010447e625bc6f9a8f1d19dec2f9c0c5719" }Generated inUsing seed: 54679 Prompt: Image of “model” standing in a stage speaking to an audience. txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9743398563840 Downloading weights 2024-08-23T14:51:49Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/0d1ee8f7bcebdf4f url=https://replicate.delivery/yhqm/d2PHCfyNb1zkWKCdVr96nzAdRXIiDvdlJsBmvOq3Ph1ztoqJA/trained_model.tar 2024-08-23T14:51:51Z | INFO | [ Complete ] dest=/src/weights-cache/0d1ee8f7bcebdf4f size="172 MB" total_elapsed=1.717s url=https://replicate.delivery/yhqm/d2PHCfyNb1zkWKCdVr96nzAdRXIiDvdlJsBmvOq3Ph1ztoqJA/trained_model.tar b'' Downloaded weights in 1.749300241470337 seconds LoRA weights loaded successfully 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:29, 1.33it/s] 5%|▌ | 2/40 [00:01<00:24, 1.52it/s] 8%|▊ | 3/40 [00:02<00:25, 1.42it/s] 10%|█ | 4/40 [00:02<00:26, 1.38it/s] 12%|█▎ | 5/40 [00:03<00:25, 1.36it/s] 15%|█▌ | 6/40 [00:04<00:25, 1.35it/s] 18%|█▊ | 7/40 [00:05<00:24, 1.34it/s] 20%|██ | 8/40 [00:05<00:24, 1.33it/s] 22%|██▎ | 9/40 [00:06<00:23, 1.33it/s] 25%|██▌ | 10/40 [00:07<00:22, 1.32it/s] 28%|██▊ | 11/40 [00:08<00:21, 1.32it/s] 30%|███ | 12/40 [00:08<00:21, 1.32it/s] 32%|███▎ | 13/40 [00:09<00:20, 1.32it/s] 35%|███▌ | 14/40 [00:10<00:19, 1.32it/s] 38%|███▊ | 15/40 [00:11<00:18, 1.32it/s] 40%|████ | 16/40 [00:11<00:18, 1.32it/s] 42%|████▎ | 17/40 [00:12<00:17, 1.32it/s] 45%|████▌ | 18/40 [00:13<00:16, 1.32it/s] 48%|████▊ | 19/40 [00:14<00:15, 1.32it/s] 50%|█████ | 20/40 [00:14<00:15, 1.32it/s] 52%|█████▎ | 21/40 [00:15<00:14, 1.32it/s] 55%|█████▌ | 22/40 [00:16<00:13, 1.32it/s] 57%|█████▊ | 23/40 [00:17<00:12, 1.32it/s] 60%|██████ | 24/40 [00:18<00:12, 1.32it/s] 62%|██████▎ | 25/40 [00:18<00:11, 1.32it/s] 65%|██████▌ | 26/40 [00:19<00:10, 1.32it/s] 68%|██████▊ | 27/40 [00:20<00:09, 1.32it/s] 70%|███████ | 28/40 [00:21<00:09, 1.32it/s] 72%|███████▎ | 29/40 [00:21<00:08, 1.32it/s] 75%|███████▌ | 30/40 [00:22<00:07, 1.32it/s] 78%|███████▊ | 31/40 [00:23<00:06, 1.32it/s] 80%|████████ | 32/40 [00:24<00:06, 1.32it/s] 82%|████████▎ | 33/40 [00:24<00:05, 1.32it/s] 85%|████████▌ | 34/40 [00:25<00:04, 1.32it/s] 88%|████████▊ | 35/40 [00:26<00:03, 1.32it/s] 90%|█████████ | 36/40 [00:27<00:03, 1.32it/s] 92%|█████████▎| 37/40 [00:27<00:02, 1.32it/s] 95%|█████████▌| 38/40 [00:28<00:01, 1.32it/s] 98%|█████████▊| 39/40 [00:29<00:00, 1.32it/s] 100%|██████████| 40/40 [00:30<00:00, 1.32it/s] 100%|██████████| 40/40 [00:30<00:00, 1.33it/s]
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