datacte / prometheusv1
PrometheusV1 is presumed to be the first full rank finetune of Playground v2.5
Prediction
datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295ID3ec07853w1rj60cgw51bxb3yn4StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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 datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", { input: { width: 1024, height: 1024, prompt: "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7, negative_prompt: "", 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 replicateImport the client:import replicateRun datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", input={ "width": 1024, "height": 1024, "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run datacte/prometheusv1 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": "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", "input": { "width": 1024, "height": 1024, "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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": "2024-07-23T20:23:23.945899Z", "created_at": "2024-07-23T20:22:39.328000Z", "data_removed": false, "error": null, "id": "3ec07853w1rj60cgw51bxb3yn4", "input": { "width": 1024, "height": 1024, "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 2531013359\nPrompt: black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:23, 2.09it/s]\n 4%|▍ | 2/50 [00:00<00:14, 3.21it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.83it/s]\n 8%|▊ | 4/50 [00:01<00:10, 4.21it/s]\n 10%|█ | 5/50 [00:01<00:10, 4.45it/s]\n 12%|█▏ | 6/50 [00:01<00:09, 4.62it/s]\n 14%|█▍ | 7/50 [00:01<00:09, 4.72it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.79it/s]\n 18%|█▊ | 9/50 [00:02<00:08, 4.84it/s]\n 20%|██ | 10/50 [00:02<00:08, 4.87it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.90it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.92it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s]\n 28%|██▊ | 14/50 [00:03<00:07, 4.94it/s]\n 30%|███ | 15/50 [00:03<00:07, 4.94it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.95it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.95it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.95it/s]\n 38%|███▊ | 19/50 [00:04<00:06, 4.95it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.95it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.95it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.95it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.95it/s]\n 48%|████▊ | 24/50 [00:05<00:05, 4.95it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.95it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.95it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.95it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.95it/s]\n 58%|█████▊ | 29/50 [00:06<00:04, 4.95it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.95it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.95it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.95it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.95it/s]\n 68%|██████▊ | 34/50 [00:07<00:03, 4.95it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.95it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.95it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.95it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.95it/s]\n 78%|███████▊ | 39/50 [00:08<00:02, 4.95it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.94it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.93it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.93it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.93it/s]\n 88%|████████▊ | 44/50 [00:09<00:01, 4.93it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.93it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.92it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.92it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.92it/s]\n 98%|█████████▊| 49/50 [00:10<00:00, 4.92it/s]\n100%|██████████| 50/50 [00:10<00:00, 5.80it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.87it/s]", "metrics": { "predict_time": 12.023515568, "total_time": 44.617899 }, "output": [ "https://replicate.delivery/yhqm/updCGWqeZKTjU6zbjmZMTT7GSebz2uDXlXKLZ3rNrKw7McLTA/out-0.png" ], "started_at": "2024-07-23T20:23:11.922383Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3ec07853w1rj60cgw51bxb3yn4", "cancel": "https://api.replicate.com/v1/predictions/3ec07853w1rj60cgw51bxb3yn4/cancel" }, "version": "a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295" }Generated inUsing seed: 2531013359 Prompt: black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:23, 2.09it/s] 4%|▍ | 2/50 [00:00<00:14, 3.21it/s] 6%|▌ | 3/50 [00:00<00:12, 3.83it/s] 8%|▊ | 4/50 [00:01<00:10, 4.21it/s] 10%|█ | 5/50 [00:01<00:10, 4.45it/s] 12%|█▏ | 6/50 [00:01<00:09, 4.62it/s] 14%|█▍ | 7/50 [00:01<00:09, 4.72it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.79it/s] 18%|█▊ | 9/50 [00:02<00:08, 4.84it/s] 20%|██ | 10/50 [00:02<00:08, 4.87it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.90it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.92it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s] 28%|██▊ | 14/50 [00:03<00:07, 4.94it/s] 30%|███ | 15/50 [00:03<00:07, 4.94it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.95it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.95it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.95it/s] 38%|███▊ | 19/50 [00:04<00:06, 4.95it/s] 40%|████ | 20/50 [00:04<00:06, 4.95it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.95it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.95it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.95it/s] 48%|████▊ | 24/50 [00:05<00:05, 4.95it/s] 50%|█████ | 25/50 [00:05<00:05, 4.95it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.95it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.95it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.95it/s] 58%|█████▊ | 29/50 [00:06<00:04, 4.95it/s] 60%|██████ | 30/50 [00:06<00:04, 4.95it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.95it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.95it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.95it/s] 68%|██████▊ | 34/50 [00:07<00:03, 4.95it/s] 70%|███████ | 35/50 [00:07<00:03, 4.95it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.95it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.95it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.95it/s] 78%|███████▊ | 39/50 [00:08<00:02, 4.95it/s] 80%|████████ | 40/50 [00:08<00:02, 4.94it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.93it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.93it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.93it/s] 88%|████████▊ | 44/50 [00:09<00:01, 4.93it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.93it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.92it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.92it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.92it/s] 98%|█████████▊| 49/50 [00:10<00:00, 4.92it/s] 100%|██████████| 50/50 [00:10<00:00, 5.80it/s] 100%|██████████| 50/50 [00:10<00:00, 4.87it/s]Prediction
datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295IDf48b2aj4r9rj00cgw52a5fvt3cStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- (impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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 datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", { input: { width: 1024, height: 1024, prompt: "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7, negative_prompt: "", 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 replicateImport the client:import replicateRun datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", input={ "width": 1024, "height": 1024, "prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run datacte/prometheusv1 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": "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", "input": { "width": 1024, "height": 1024, "prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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": "2024-07-23T20:24:37.337665Z", "created_at": "2024-07-23T20:24:26.050000Z", "data_removed": false, "error": null, "id": "f48b2aj4r9rj00cgw52a5fvt3c", "input": { "width": 1024, "height": 1024, "prompt": "(impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 4203669156\nPrompt: (impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers\ntxt2img mode\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['feeling cool, drunk on plum wine, masterpiece, 8 k, hyper detailed, smokey ambiance, perfect hands and fingers']\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['feeling cool, drunk on plum wine, masterpiece, 8 k, hyper detailed, smokey ambiance, perfect hands and fingers']\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.39it/s]\n 4%|▍ | 2/50 [00:00<00:08, 5.45it/s]\n 6%|▌ | 3/50 [00:00<00:09, 5.19it/s]\n 8%|▊ | 4/50 [00:00<00:09, 5.08it/s]\n 10%|█ | 5/50 [00:00<00:08, 5.02it/s]\n 12%|█▏ | 6/50 [00:01<00:08, 4.98it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.95it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.94it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s]\n 20%|██ | 10/50 [00:01<00:08, 4.94it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.94it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.94it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.94it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.93it/s]\n 30%|███ | 15/50 [00:02<00:07, 4.93it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.93it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.92it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.92it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.91it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.91it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.91it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.91it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.91it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.91it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.91it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.92it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.92it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.92it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.92it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.92it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.91it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.91it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.91it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.90it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.90it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.90it/s]\n 78%|███████▊ | 39/50 [00:07<00:02, 4.91it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.91it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.91it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.92it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.91it/s]\n 88%|████████▊ | 44/50 [00:08<00:01, 4.91it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.91it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.90it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.90it/s]\n 98%|█████████▊| 49/50 [00:09<00:00, 4.90it/s]\n100%|██████████| 50/50 [00:10<00:00, 5.78it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.99it/s]", "metrics": { "predict_time": 11.279413923, "total_time": 11.287665 }, "output": [ "https://replicate.delivery/yhqm/gdge4qfF8PuNcU2XkgJozIhdoWR5wIs4LtCe2HoCVUxIc4WmA/out-0.png" ], "started_at": "2024-07-23T20:24:26.058252Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/f48b2aj4r9rj00cgw52a5fvt3c", "cancel": "https://api.replicate.com/v1/predictions/f48b2aj4r9rj00cgw52a5fvt3c/cancel" }, "version": "a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295" }Generated inUsing seed: 4203669156 Prompt: (impressionistic realism by csybgh), a 50 something male, working in banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry, talks a lot but listens poorly, stuck in the past, wearing a suit, he has a certain charm, bronze skintone, sitting in a bar at night, he is smoking and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed, smokey ambiance, perfect hands AND fingers txt2img mode The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['feeling cool, drunk on plum wine, masterpiece, 8 k, hyper detailed, smokey ambiance, perfect hands and fingers'] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['feeling cool, drunk on plum wine, masterpiece, 8 k, hyper detailed, smokey ambiance, perfect hands and fingers'] 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.39it/s] 4%|▍ | 2/50 [00:00<00:08, 5.45it/s] 6%|▌ | 3/50 [00:00<00:09, 5.19it/s] 8%|▊ | 4/50 [00:00<00:09, 5.08it/s] 10%|█ | 5/50 [00:00<00:08, 5.02it/s] 12%|█▏ | 6/50 [00:01<00:08, 4.98it/s] 14%|█▍ | 7/50 [00:01<00:08, 4.95it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.94it/s] 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s] 20%|██ | 10/50 [00:01<00:08, 4.94it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.94it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.94it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.94it/s] 28%|██▊ | 14/50 [00:02<00:07, 4.93it/s] 30%|███ | 15/50 [00:02<00:07, 4.93it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.93it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.92it/s] 38%|███▊ | 19/50 [00:03<00:06, 4.92it/s] 40%|████ | 20/50 [00:04<00:06, 4.91it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.91it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.91it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.91it/s] 48%|████▊ | 24/50 [00:04<00:05, 4.91it/s] 50%|█████ | 25/50 [00:05<00:05, 4.91it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.91it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.92it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.92it/s] 58%|█████▊ | 29/50 [00:05<00:04, 4.92it/s] 60%|██████ | 30/50 [00:06<00:04, 4.92it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.92it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.91it/s] 68%|██████▊ | 34/50 [00:06<00:03, 4.91it/s] 70%|███████ | 35/50 [00:07<00:03, 4.91it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.90it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.90it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.90it/s] 78%|███████▊ | 39/50 [00:07<00:02, 4.91it/s] 80%|████████ | 40/50 [00:08<00:02, 4.91it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.91it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.92it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.91it/s] 88%|████████▊ | 44/50 [00:08<00:01, 4.91it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.91it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.90it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.90it/s] 98%|█████████▊| 49/50 [00:09<00:00, 4.90it/s] 100%|██████████| 50/50 [00:10<00:00, 5.78it/s] 100%|██████████| 50/50 [00:10<00:00, 4.99it/s]Prediction
datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295IDhnwb31zpcsrj20cgw52r7kkd50StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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 datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", { input: { width: 1024, height: 1024, prompt: "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7, negative_prompt: "", 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 replicateImport the client:import replicateRun datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", input={ "width": 1024, "height": 1024, "prompt": "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run datacte/prometheusv1 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": "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", "input": { "width": 1024, "height": 1024, "prompt": "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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": "2024-07-23T20:26:28.194897Z", "created_at": "2024-07-23T20:26:17.062000Z", "data_removed": false, "error": null, "id": "hnwb31zpcsrj20cgw52r7kkd50", "input": { "width": 1024, "height": 1024, "prompt": "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 4074402560\nPrompt: high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette\ntxt2img mode\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['a strong use of negative space. the entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. silhouette']\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['a strong use of negative space. the entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. silhouette']\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.42it/s]\n 4%|▍ | 2/50 [00:00<00:08, 5.47it/s]\n 6%|▌ | 3/50 [00:00<00:08, 5.22it/s]\n 8%|▊ | 4/50 [00:00<00:08, 5.11it/s]\n 10%|█ | 5/50 [00:00<00:08, 5.05it/s]\n 12%|█▏ | 6/50 [00:01<00:08, 5.01it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.98it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.96it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s]\n 20%|██ | 10/50 [00:01<00:08, 4.94it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.93it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.93it/s]\n 30%|███ | 15/50 [00:02<00:07, 4.93it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.93it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.93it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.93it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.93it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.93it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.93it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.92it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.92it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.91it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.90it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.90it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.90it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.91it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.91it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.91it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.92it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.92it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.91it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.91it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.91it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.90it/s]\n 78%|███████▊ | 39/50 [00:07<00:02, 4.90it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.90it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.90it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.91it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.91it/s]\n 88%|████████▊ | 44/50 [00:08<00:01, 4.91it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.91it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.91it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.91it/s]\n 98%|█████████▊| 49/50 [00:09<00:00, 4.91it/s]\n100%|██████████| 50/50 [00:10<00:00, 5.78it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.99it/s]", "metrics": { "predict_time": 11.124381258, "total_time": 11.132897 }, "output": [ "https://replicate.delivery/yhqm/3YNdyFH4QgJ8EBjVvhv8HmyQhOfvyOEZppgz3cDGbGy5HulJA/out-0.png" ], "started_at": "2024-07-23T20:26:17.070516Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hnwb31zpcsrj20cgw52r7kkd50", "cancel": "https://api.replicate.com/v1/predictions/hnwb31zpcsrj20cgw52r7kkd50/cancel" }, "version": "a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295" }Generated inUsing seed: 4074402560 Prompt: high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette txt2img mode The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['a strong use of negative space. the entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. silhouette'] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['a strong use of negative space. the entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. silhouette'] 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.42it/s] 4%|▍ | 2/50 [00:00<00:08, 5.47it/s] 6%|▌ | 3/50 [00:00<00:08, 5.22it/s] 8%|▊ | 4/50 [00:00<00:08, 5.11it/s] 10%|█ | 5/50 [00:00<00:08, 5.05it/s] 12%|█▏ | 6/50 [00:01<00:08, 5.01it/s] 14%|█▍ | 7/50 [00:01<00:08, 4.98it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.96it/s] 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s] 20%|██ | 10/50 [00:01<00:08, 4.94it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.93it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s] 28%|██▊ | 14/50 [00:02<00:07, 4.93it/s] 30%|███ | 15/50 [00:02<00:07, 4.93it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.93it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.93it/s] 38%|███▊ | 19/50 [00:03<00:06, 4.93it/s] 40%|████ | 20/50 [00:04<00:06, 4.93it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.93it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.93it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.92it/s] 48%|████▊ | 24/50 [00:04<00:05, 4.92it/s] 50%|█████ | 25/50 [00:05<00:05, 4.91it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.90it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.90it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.90it/s] 58%|█████▊ | 29/50 [00:05<00:04, 4.91it/s] 60%|██████ | 30/50 [00:06<00:04, 4.91it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.91it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.92it/s] 68%|██████▊ | 34/50 [00:06<00:03, 4.92it/s] 70%|███████ | 35/50 [00:07<00:03, 4.91it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.91it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.91it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.90it/s] 78%|███████▊ | 39/50 [00:07<00:02, 4.90it/s] 80%|████████ | 40/50 [00:08<00:02, 4.90it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.90it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.91it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.91it/s] 88%|████████▊ | 44/50 [00:08<00:01, 4.91it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.91it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.91it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.91it/s] 98%|█████████▊| 49/50 [00:09<00:00, 4.91it/s] 100%|██████████| 50/50 [00:10<00:00, 5.78it/s] 100%|██████████| 50/50 [00:10<00:00, 4.99it/s]Prediction
datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295IDqc6mtnt509rj20cgw53bjf4160StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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 datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", { input: { width: 1024, height: 1024, prompt: "The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7, negative_prompt: "", 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 replicateImport the client:import replicateRun datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", input={ "width": 1024, "height": 1024, "prompt": "The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run datacte/prometheusv1 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": "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", "input": { "width": 1024, "height": 1024, "prompt": "The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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": "2024-07-23T20:26:48.437867Z", "created_at": "2024-07-23T20:26:37.186000Z", "data_removed": false, "error": null, "id": "qc6mtnt509rj20cgw53bjf4160", "input": { "width": 1024, "height": 1024, "prompt": "The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 1888282877\nPrompt: The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.39it/s]\n 4%|▍ | 2/50 [00:00<00:08, 5.46it/s]\n 6%|▌ | 3/50 [00:00<00:09, 5.21it/s]\n 8%|▊ | 4/50 [00:00<00:09, 5.11it/s]\n 10%|█ | 5/50 [00:00<00:08, 5.04it/s]\n 12%|█▏ | 6/50 [00:01<00:08, 5.00it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.97it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.95it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s]\n 20%|██ | 10/50 [00:01<00:08, 4.93it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.93it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.93it/s]\n 30%|███ | 15/50 [00:02<00:07, 4.93it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.93it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.94it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.94it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.93it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.93it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.93it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.93it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.92it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.92it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.92it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.91it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.91it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.91it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.92it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.91it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.92it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.92it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.92it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.93it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.93it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.92it/s]\n 78%|███████▊ | 39/50 [00:07<00:02, 4.92it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.92it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.91it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.91it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.90it/s]\n 88%|████████▊ | 44/50 [00:08<00:01, 4.90it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.91it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.91it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.91it/s]\n 98%|█████████▊| 49/50 [00:09<00:00, 4.91it/s]\n100%|██████████| 50/50 [00:10<00:00, 5.79it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.99it/s]", "metrics": { "predict_time": 11.244712275, "total_time": 11.251867 }, "output": [ "https://replicate.delivery/yhqm/KpMn8I73t1JENNHuaibGglNHmfy7XdVMFAU56EE369NEIulJA/out-0.png" ], "started_at": "2024-07-23T20:26:37.193155Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/qc6mtnt509rj20cgw53bjf4160", "cancel": "https://api.replicate.com/v1/predictions/qc6mtnt509rj20cgw53bjf4160/cancel" }, "version": "a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295" }Generated inUsing seed: 1888282877 Prompt: The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze. txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.39it/s] 4%|▍ | 2/50 [00:00<00:08, 5.46it/s] 6%|▌ | 3/50 [00:00<00:09, 5.21it/s] 8%|▊ | 4/50 [00:00<00:09, 5.11it/s] 10%|█ | 5/50 [00:00<00:08, 5.04it/s] 12%|█▏ | 6/50 [00:01<00:08, 5.00it/s] 14%|█▍ | 7/50 [00:01<00:08, 4.97it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.95it/s] 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s] 20%|██ | 10/50 [00:01<00:08, 4.93it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.93it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s] 28%|██▊ | 14/50 [00:02<00:07, 4.93it/s] 30%|███ | 15/50 [00:02<00:07, 4.93it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.93it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.94it/s] 38%|███▊ | 19/50 [00:03<00:06, 4.94it/s] 40%|████ | 20/50 [00:04<00:06, 4.93it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.93it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.93it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.93it/s] 48%|████▊ | 24/50 [00:04<00:05, 4.92it/s] 50%|█████ | 25/50 [00:05<00:05, 4.92it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.92it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.91it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.91it/s] 58%|█████▊ | 29/50 [00:05<00:04, 4.91it/s] 60%|██████ | 30/50 [00:06<00:04, 4.92it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.91it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.92it/s] 68%|██████▊ | 34/50 [00:06<00:03, 4.92it/s] 70%|███████ | 35/50 [00:07<00:03, 4.92it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.93it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.93it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.92it/s] 78%|███████▊ | 39/50 [00:07<00:02, 4.92it/s] 80%|████████ | 40/50 [00:08<00:02, 4.92it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.91it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.91it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.90it/s] 88%|████████▊ | 44/50 [00:08<00:01, 4.90it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.91it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.91it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.91it/s] 98%|█████████▊| 49/50 [00:09<00:00, 4.91it/s] 100%|██████████| 50/50 [00:10<00:00, 5.79it/s] 100%|██████████| 50/50 [00:10<00:00, 4.99it/s]Prediction
datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295IDnmyt0cw7d9rj60cgw53a5n4xp0StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne d'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne d'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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 datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", { input: { width: 1024, height: 1024, prompt: "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne d'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7, negative_prompt: "", 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 replicateImport the client:import replicateRun datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", input={ "width": 1024, "height": 1024, "prompt": "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne d'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run datacte/prometheusv1 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": "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", "input": { "width": 1024, "height": 1024, "prompt": "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne d\'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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": "2024-07-23T20:27:05.349517Z", "created_at": "2024-07-23T20:26:54.186000Z", "data_removed": false, "error": null, "id": "nmyt0cw7d9rj60cgw53a5n4xp0", "input": { "width": 1024, "height": 1024, "prompt": "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne d'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 324658228\nPrompt: Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne d'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.39it/s]\n 4%|▍ | 2/50 [00:00<00:08, 5.46it/s]\n 6%|▌ | 3/50 [00:00<00:09, 5.21it/s]\n 8%|▊ | 4/50 [00:00<00:09, 5.11it/s]\n 10%|█ | 5/50 [00:00<00:08, 5.05it/s]\n 12%|█▏ | 6/50 [00:01<00:08, 5.01it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.98it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.96it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s]\n 20%|██ | 10/50 [00:01<00:08, 4.94it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.93it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.92it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.92it/s]\n 30%|███ | 15/50 [00:02<00:07, 4.92it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.92it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.92it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.92it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.92it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.92it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.92it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.92it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.92it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.93it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.93it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.93it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.93it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.93it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.93it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.92it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.92it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.92it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.92it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.92it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.92it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.91it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.91it/s]\n 78%|███████▊ | 39/50 [00:07<00:02, 4.90it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.90it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.90it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.90it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.90it/s]\n 88%|████████▊ | 44/50 [00:08<00:01, 4.90it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.91it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.91it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.91it/s]\n 98%|█████████▊| 49/50 [00:09<00:00, 4.91it/s]\n100%|██████████| 50/50 [00:10<00:00, 5.78it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.99it/s]", "metrics": { "predict_time": 11.154458025, "total_time": 11.163517 }, "output": [ "https://replicate.delivery/yhqm/4QMwRbL6DiYNPhBwer5Ol1tB4059dmpy1jOiPfpwf17zg4WmA/out-0.png" ], "started_at": "2024-07-23T20:26:54.195059Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nmyt0cw7d9rj60cgw53a5n4xp0", "cancel": "https://api.replicate.com/v1/predictions/nmyt0cw7d9rj60cgw53a5n4xp0/cancel" }, "version": "a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295" }Generated inUsing seed: 324658228 Prompt: Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne d'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.39it/s] 4%|▍ | 2/50 [00:00<00:08, 5.46it/s] 6%|▌ | 3/50 [00:00<00:09, 5.21it/s] 8%|▊ | 4/50 [00:00<00:09, 5.11it/s] 10%|█ | 5/50 [00:00<00:08, 5.05it/s] 12%|█▏ | 6/50 [00:01<00:08, 5.01it/s] 14%|█▍ | 7/50 [00:01<00:08, 4.98it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.96it/s] 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s] 20%|██ | 10/50 [00:01<00:08, 4.94it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.93it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.92it/s] 28%|██▊ | 14/50 [00:02<00:07, 4.92it/s] 30%|███ | 15/50 [00:02<00:07, 4.92it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.92it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.92it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.92it/s] 38%|███▊ | 19/50 [00:03<00:06, 4.92it/s] 40%|████ | 20/50 [00:04<00:06, 4.92it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.92it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.92it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.92it/s] 48%|████▊ | 24/50 [00:04<00:05, 4.93it/s] 50%|█████ | 25/50 [00:05<00:05, 4.93it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.93it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.93it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.93it/s] 58%|█████▊ | 29/50 [00:05<00:04, 4.93it/s] 60%|██████ | 30/50 [00:06<00:04, 4.92it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.92it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.92it/s] 68%|██████▊ | 34/50 [00:06<00:03, 4.92it/s] 70%|███████ | 35/50 [00:07<00:03, 4.92it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.92it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.91it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.91it/s] 78%|███████▊ | 39/50 [00:07<00:02, 4.90it/s] 80%|████████ | 40/50 [00:08<00:02, 4.90it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.90it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.90it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.90it/s] 88%|████████▊ | 44/50 [00:08<00:01, 4.90it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.91it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.91it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.91it/s] 98%|█████████▊| 49/50 [00:09<00:00, 4.91it/s] 100%|██████████| 50/50 [00:10<00:00, 5.78it/s] 100%|██████████| 50/50 [00:10<00:00, 4.99it/s]Prediction
datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295IDq654c18939rj20cgw53tg44vvmStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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 datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", { input: { width: 1024, height: 1024, prompt: "cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7, negative_prompt: "", 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 replicateImport the client:import replicateRun datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", input={ "width": 1024, "height": 1024, "prompt": "cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run datacte/prometheusv1 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": "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", "input": { "width": 1024, "height": 1024, "prompt": "cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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": "2024-07-23T20:27:38.550270Z", "created_at": "2024-07-23T20:27:27.386000Z", "data_removed": false, "error": null, "id": "q654c18939rj20cgw53tg44vvm", "input": { "width": 1024, "height": 1024, "prompt": "cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 655685162\nPrompt: cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.38it/s]\n 4%|▍ | 2/50 [00:00<00:08, 5.45it/s]\n 6%|▌ | 3/50 [00:00<00:09, 5.21it/s]\n 8%|▊ | 4/50 [00:00<00:09, 5.09it/s]\n 10%|█ | 5/50 [00:00<00:08, 5.04it/s]\n 12%|█▏ | 6/50 [00:01<00:08, 5.01it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.97it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.95it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s]\n 20%|██ | 10/50 [00:01<00:08, 4.93it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.92it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.92it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.92it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.91it/s]\n 30%|███ | 15/50 [00:03<00:07, 4.92it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.92it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.93it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.93it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.93it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.93it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.92it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.92it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.92it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.92it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.92it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.91it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.91it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.91it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.90it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.91it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.91it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.91it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.91it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.91it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.91it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.91it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.92it/s]\n 78%|███████▊ | 39/50 [00:07<00:02, 4.91it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.91it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.91it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.91it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.91it/s]\n 88%|████████▊ | 44/50 [00:08<00:01, 4.91it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.90it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.90it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.90it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.90it/s]\n 98%|█████████▊| 49/50 [00:09<00:00, 4.90it/s]\n100%|██████████| 50/50 [00:10<00:00, 5.78it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.99it/s]", "metrics": { "predict_time": 11.156457635, "total_time": 11.16427 }, "output": [ "https://replicate.delivery/yhqm/qszSQImOsnKdPJ9VJse6dKdUnL2CbGuPbeJDI3g4Nu26QcLTA/out-0.png" ], "started_at": "2024-07-23T20:27:27.393812Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/q654c18939rj20cgw53tg44vvm", "cancel": "https://api.replicate.com/v1/predictions/q654c18939rj20cgw53tg44vvm/cancel" }, "version": "a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295" }Generated inUsing seed: 655685162 Prompt: cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.38it/s] 4%|▍ | 2/50 [00:00<00:08, 5.45it/s] 6%|▌ | 3/50 [00:00<00:09, 5.21it/s] 8%|▊ | 4/50 [00:00<00:09, 5.09it/s] 10%|█ | 5/50 [00:00<00:08, 5.04it/s] 12%|█▏ | 6/50 [00:01<00:08, 5.01it/s] 14%|█▍ | 7/50 [00:01<00:08, 4.97it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.95it/s] 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s] 20%|██ | 10/50 [00:01<00:08, 4.93it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.92it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.92it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.92it/s] 28%|██▊ | 14/50 [00:02<00:07, 4.91it/s] 30%|███ | 15/50 [00:03<00:07, 4.92it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.92it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.93it/s] 38%|███▊ | 19/50 [00:03<00:06, 4.93it/s] 40%|████ | 20/50 [00:04<00:06, 4.93it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.93it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.92it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.92it/s] 48%|████▊ | 24/50 [00:04<00:05, 4.92it/s] 50%|█████ | 25/50 [00:05<00:05, 4.92it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.92it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.91it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.91it/s] 58%|█████▊ | 29/50 [00:05<00:04, 4.91it/s] 60%|██████ | 30/50 [00:06<00:04, 4.90it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.91it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.91it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.91it/s] 68%|██████▊ | 34/50 [00:06<00:03, 4.91it/s] 70%|███████ | 35/50 [00:07<00:03, 4.91it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.91it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.91it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.92it/s] 78%|███████▊ | 39/50 [00:07<00:02, 4.91it/s] 80%|████████ | 40/50 [00:08<00:02, 4.91it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.91it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.91it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.91it/s] 88%|████████▊ | 44/50 [00:08<00:01, 4.91it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.90it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.90it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.90it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.90it/s] 98%|█████████▊| 49/50 [00:09<00:00, 4.90it/s] 100%|██████████| 50/50 [00:10<00:00, 5.78it/s] 100%|██████████| 50/50 [00:10<00:00, 4.99it/s]Prediction
datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295ID5fxseetddhrj40cgw53rjd086wStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- 1980s anime portrait of a character
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "1980s anime portrait of a character ", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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 datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", { input: { width: 1024, height: 1024, prompt: "1980s anime portrait of a character ", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7, negative_prompt: "", 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 replicateImport the client:import replicateRun datacte/prometheusv1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", input={ "width": 1024, "height": 1024, "prompt": "1980s anime portrait of a character ", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run datacte/prometheusv1 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": "datacte/prometheusv1:a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295", "input": { "width": 1024, "height": 1024, "prompt": "1980s anime portrait of a character ", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "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": "2024-07-23T20:27:56.162034Z", "created_at": "2024-07-23T20:27:44.876000Z", "data_removed": false, "error": null, "id": "5fxseetddhrj40cgw53rjd086w", "input": { "width": 1024, "height": 1024, "prompt": "1980s anime portrait of a character ", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 2039729168\nPrompt: 1980s anime portrait of a character\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.39it/s]\n 4%|▍ | 2/50 [00:00<00:08, 5.46it/s]\n 6%|▌ | 3/50 [00:00<00:09, 5.22it/s]\n 8%|▊ | 4/50 [00:00<00:09, 5.10it/s]\n 10%|█ | 5/50 [00:00<00:08, 5.04it/s]\n 12%|█▏ | 6/50 [00:01<00:08, 5.00it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.97it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.95it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s]\n 20%|██ | 10/50 [00:01<00:08, 4.93it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.93it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.93it/s]\n 30%|███ | 15/50 [00:02<00:07, 4.92it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.93it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.93it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.93it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.93it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.93it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.92it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.92it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.92it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.91it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.90it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.90it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.91it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.91it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.91it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.91it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.91it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.91it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.91it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.91it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.91it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.91it/s]\n 78%|███████▊ | 39/50 [00:07<00:02, 4.91it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.91it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.91it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.92it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.92it/s]\n 88%|████████▊ | 44/50 [00:08<00:01, 4.92it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.92it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.91it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.91it/s]\n 98%|█████████▊| 49/50 [00:09<00:00, 4.90it/s]\n100%|██████████| 50/50 [00:10<00:00, 5.77it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.99it/s]", "metrics": { "predict_time": 11.279661154, "total_time": 11.286034 }, "output": [ "https://replicate.delivery/yhqm/sYddbUullVpzBhdGrY5x3gFLovBVqgPPW3fjFYHPeYjLRcLTA/out-0.png" ], "started_at": "2024-07-23T20:27:44.882372Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5fxseetddhrj40cgw53rjd086w", "cancel": "https://api.replicate.com/v1/predictions/5fxseetddhrj40cgw53rjd086w/cancel" }, "version": "a40536dd5f61e7c3c43060dff5b9b488a749dec1cb283a904dd82032fc717295" }Generated inUsing seed: 2039729168 Prompt: 1980s anime portrait of a character txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.39it/s] 4%|▍ | 2/50 [00:00<00:08, 5.46it/s] 6%|▌ | 3/50 [00:00<00:09, 5.22it/s] 8%|▊ | 4/50 [00:00<00:09, 5.10it/s] 10%|█ | 5/50 [00:00<00:08, 5.04it/s] 12%|█▏ | 6/50 [00:01<00:08, 5.00it/s] 14%|█▍ | 7/50 [00:01<00:08, 4.97it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.95it/s] 18%|█▊ | 9/50 [00:01<00:08, 4.94it/s] 20%|██ | 10/50 [00:01<00:08, 4.93it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.93it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.93it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.93it/s] 28%|██▊ | 14/50 [00:02<00:07, 4.93it/s] 30%|███ | 15/50 [00:02<00:07, 4.92it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.93it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.93it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.93it/s] 38%|███▊ | 19/50 [00:03<00:06, 4.93it/s] 40%|████ | 20/50 [00:04<00:06, 4.93it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.93it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.92it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.92it/s] 48%|████▊ | 24/50 [00:04<00:05, 4.92it/s] 50%|█████ | 25/50 [00:05<00:05, 4.91it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.90it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.90it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.91it/s] 58%|█████▊ | 29/50 [00:05<00:04, 4.91it/s] 60%|██████ | 30/50 [00:06<00:04, 4.91it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.91it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.92it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.91it/s] 68%|██████▊ | 34/50 [00:06<00:03, 4.91it/s] 70%|███████ | 35/50 [00:07<00:03, 4.91it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.91it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.91it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.91it/s] 78%|███████▊ | 39/50 [00:07<00:02, 4.91it/s] 80%|████████ | 40/50 [00:08<00:02, 4.91it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.91it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.92it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.92it/s] 88%|████████▊ | 44/50 [00:08<00:01, 4.92it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.92it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.91it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.91it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.91it/s] 98%|█████████▊| 49/50 [00:09<00:00, 4.90it/s] 100%|██████████| 50/50 [00:10<00:00, 5.77it/s] 100%|██████████| 50/50 [00:10<00:00, 4.99it/s]
Want to make some of these yourself?
Run this model
