heywowyou / heywowflux
(Updated 8 months, 2 weeks ago)
- Public
- 1.1K runs
-
H100
Prediction
heywowyou/heywowflux:8a1507c19343eb7a0d24aee280f523f213bb8825c52e8c470beb40a672eca4d8IDerr5nefvyxrj00cj6zp9db7zegStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- model
- dev
- prompt
- HENRIK_PURIENNE photographs a young woman. Full body shot.
- lora_scale
- 1
- num_outputs
- 3
- aspect_ratio
- 4:5
- output_format
- png
- guidance_scale
- 1.5
- output_quality
- 90
- prompt_strength
- 1
- extra_lora_scale
- 1
- num_inference_steps
- 50
{ "model": "dev", "prompt": "HENRIK_PURIENNE photographs a young woman. Full body shot.", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 1.5, "output_quality": 90, "prompt_strength": 1, "extra_lora_scale": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run heywowyou/heywowflux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "heywowyou/heywowflux:8a1507c19343eb7a0d24aee280f523f213bb8825c52e8c470beb40a672eca4d8", { input: { model: "dev", prompt: "HENRIK_PURIENNE photographs a young woman. Full body shot.", lora_scale: 1, num_outputs: 3, aspect_ratio: "4:5", output_format: "png", guidance_scale: 1.5, output_quality: 90, prompt_strength: 1, extra_lora_scale: 1, 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 heywowyou/heywowflux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "heywowyou/heywowflux:8a1507c19343eb7a0d24aee280f523f213bb8825c52e8c470beb40a672eca4d8", input={ "model": "dev", "prompt": "HENRIK_PURIENNE photographs a young woman. Full body shot.", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 1.5, "output_quality": 90, "prompt_strength": 1, "extra_lora_scale": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run heywowyou/heywowflux 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": "heywowyou/heywowflux:8a1507c19343eb7a0d24aee280f523f213bb8825c52e8c470beb40a672eca4d8", "input": { "model": "dev", "prompt": "HENRIK_PURIENNE photographs a young woman. Full body shot.", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 1.5, "output_quality": 90, "prompt_strength": 1, "extra_lora_scale": 1, "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": "2024-09-28T09:20:25.719614Z", "created_at": "2024-09-28T09:18:50.871000Z", "data_removed": false, "error": null, "id": "err5nefvyxrj00cj6zp9db7zeg", "input": { "model": "dev", "prompt": "HENRIK_PURIENNE photographs a young woman. Full body shot.", "lora_scale": 1, "num_outputs": 3, "aspect_ratio": "4:5", "output_format": "png", "guidance_scale": 1.5, "output_quality": 90, "prompt_strength": 1, "extra_lora_scale": 1, "num_inference_steps": 50 }, "logs": "Using seed: 22124\nPrompt: HENRIK_PURIENNE photographs a young woman. Full body shot.\n[!] txt2img mode\nUsing dev model\nfree=4952481665024\nDownloading weights\n2024-09-28T09:18:52Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpm628agor/weights url=https://replicate.delivery/yhqm/rBiOuCnDLm42CJkPmgyNhqDDkTsa30jupAOMmNQjz3WcuV4E/trained_model.tar\n2024-09-28T09:18:53Z | INFO | [ Complete ] dest=/tmp/tmpm628agor/weights size=\"172 MB\" total_elapsed=1.236s url=https://replicate.delivery/yhqm/rBiOuCnDLm42CJkPmgyNhqDDkTsa30jupAOMmNQjz3WcuV4E/trained_model.tar\nDownloaded weights in 1.27s\nLoaded LoRAs in 2.06s\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:01<01:26, 1.77s/it]\n 4%|▍ | 2/50 [00:03<01:14, 1.56s/it]\n 6%|▌ | 3/50 [00:04<01:17, 1.66s/it]\n 8%|▊ | 4/50 [00:06<01:18, 1.70s/it]\n 10%|█ | 5/50 [00:08<01:17, 1.73s/it]\n 12%|█▏ | 6/50 [00:10<01:16, 1.74s/it]\n 14%|█▍ | 7/50 [00:12<01:15, 1.75s/it]\n 16%|█▌ | 8/50 [00:13<01:13, 1.76s/it]\n 18%|█▊ | 9/50 [00:15<01:12, 1.76s/it]\n 20%|██ | 10/50 [00:17<01:10, 1.76s/it]\n 22%|██▏ | 11/50 [00:19<01:08, 1.77s/it]\n 24%|██▍ | 12/50 [00:20<01:07, 1.77s/it]\n 26%|██▌ | 13/50 [00:22<01:05, 1.77s/it]\n 28%|██▊ | 14/50 [00:24<01:03, 1.77s/it]\n 30%|███ | 15/50 [00:26<01:02, 1.77s/it]\n 32%|███▏ | 16/50 [00:27<01:00, 1.78s/it]\n 34%|███▍ | 17/50 [00:29<00:58, 1.78s/it]\n 36%|███▌ | 18/50 [00:31<00:56, 1.78s/it]\n 38%|███▊ | 19/50 [00:33<00:55, 1.78s/it]\n 40%|████ | 20/50 [00:35<00:53, 1.78s/it]\n 42%|████▏ | 21/50 [00:36<00:51, 1.78s/it]\n 44%|████▍ | 22/50 [00:38<00:49, 1.78s/it]\n 46%|████▌ | 23/50 [00:40<00:48, 1.78s/it]\n 48%|████▊ | 24/50 [00:42<00:46, 1.78s/it]\n 50%|█████ | 25/50 [00:43<00:44, 1.78s/it]\n 52%|█████▏ | 26/50 [00:45<00:42, 1.78s/it]\n 54%|█████▍ | 27/50 [00:47<00:40, 1.78s/it]\n 56%|█████▌ | 28/50 [00:49<00:39, 1.78s/it]\n 58%|█████▊ | 29/50 [00:51<00:37, 1.78s/it]\n 60%|██████ | 30/50 [00:52<00:35, 1.78s/it]\n 62%|██████▏ | 31/50 [00:54<00:33, 1.78s/it]\n 64%|██████▍ | 32/50 [00:56<00:32, 1.78s/it]\n 66%|██████▌ | 33/50 [00:58<00:30, 1.78s/it]\n 68%|██████▊ | 34/50 [01:00<00:28, 1.78s/it]\n 70%|███████ | 35/50 [01:01<00:26, 1.78s/it]\n 72%|███████▏ | 36/50 [01:03<00:24, 1.78s/it]\n 74%|███████▍ | 37/50 [01:05<00:23, 1.78s/it]\n 76%|███████▌ | 38/50 [01:07<00:21, 1.78s/it]\n 78%|███████▊ | 39/50 [01:08<00:19, 1.78s/it]\n 80%|████████ | 40/50 [01:10<00:17, 1.78s/it]\n 82%|████████▏ | 41/50 [01:12<00:16, 1.78s/it]\n 84%|████████▍ | 42/50 [01:14<00:14, 1.78s/it]\n 86%|████████▌ | 43/50 [01:16<00:12, 1.78s/it]\n 88%|████████▊ | 44/50 [01:17<00:10, 1.78s/it]\n 90%|█████████ | 45/50 [01:19<00:08, 1.78s/it]\n 92%|█████████▏| 46/50 [01:21<00:07, 1.78s/it]\n 94%|█████████▍| 47/50 [01:23<00:05, 1.78s/it]\n 96%|█████████▌| 48/50 [01:24<00:03, 1.78s/it]\n 98%|█████████▊| 49/50 [01:26<00:01, 1.78s/it]\n100%|██████████| 50/50 [01:28<00:00, 1.78s/it]\n100%|██████████| 50/50 [01:28<00:00, 1.77s/it]", "metrics": { "predict_time": 93.66630267, "total_time": 94.848614 }, "output": [ "https://replicate.delivery/yhqm/IVEYseRLkCwFN6TlePVK660bghUe1UdITRbReqkDc31hFfKcC/out-0.png", "https://replicate.delivery/yhqm/KwequnJaIfjCd04Lv3MgSOJALovG46lfEllvxEIzRFwzivCnA/out-1.png", "https://replicate.delivery/yhqm/xtBWBMjoPGI4N1fEK1jJy8heulgfOQ2uVaMUlwQkDjkzivCnA/out-2.png" ], "started_at": "2024-09-28T09:18:52.053311Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/err5nefvyxrj00cj6zp9db7zeg", "cancel": "https://api.replicate.com/v1/predictions/err5nefvyxrj00cj6zp9db7zeg/cancel" }, "version": "8a1507c19343eb7a0d24aee280f523f213bb8825c52e8c470beb40a672eca4d8" }Generated inUsing seed: 22124 Prompt: HENRIK_PURIENNE photographs a young woman. Full body shot. [!] txt2img mode Using dev model free=4952481665024 Downloading weights 2024-09-28T09:18:52Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpm628agor/weights url=https://replicate.delivery/yhqm/rBiOuCnDLm42CJkPmgyNhqDDkTsa30jupAOMmNQjz3WcuV4E/trained_model.tar 2024-09-28T09:18:53Z | INFO | [ Complete ] dest=/tmp/tmpm628agor/weights size="172 MB" total_elapsed=1.236s url=https://replicate.delivery/yhqm/rBiOuCnDLm42CJkPmgyNhqDDkTsa30jupAOMmNQjz3WcuV4E/trained_model.tar Downloaded weights in 1.27s Loaded LoRAs in 2.06s 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<01:26, 1.77s/it] 4%|▍ | 2/50 [00:03<01:14, 1.56s/it] 6%|▌ | 3/50 [00:04<01:17, 1.66s/it] 8%|▊ | 4/50 [00:06<01:18, 1.70s/it] 10%|█ | 5/50 [00:08<01:17, 1.73s/it] 12%|█▏ | 6/50 [00:10<01:16, 1.74s/it] 14%|█▍ | 7/50 [00:12<01:15, 1.75s/it] 16%|█▌ | 8/50 [00:13<01:13, 1.76s/it] 18%|█▊ | 9/50 [00:15<01:12, 1.76s/it] 20%|██ | 10/50 [00:17<01:10, 1.76s/it] 22%|██▏ | 11/50 [00:19<01:08, 1.77s/it] 24%|██▍ | 12/50 [00:20<01:07, 1.77s/it] 26%|██▌ | 13/50 [00:22<01:05, 1.77s/it] 28%|██▊ | 14/50 [00:24<01:03, 1.77s/it] 30%|███ | 15/50 [00:26<01:02, 1.77s/it] 32%|███▏ | 16/50 [00:27<01:00, 1.78s/it] 34%|███▍ | 17/50 [00:29<00:58, 1.78s/it] 36%|███▌ | 18/50 [00:31<00:56, 1.78s/it] 38%|███▊ | 19/50 [00:33<00:55, 1.78s/it] 40%|████ | 20/50 [00:35<00:53, 1.78s/it] 42%|████▏ | 21/50 [00:36<00:51, 1.78s/it] 44%|████▍ | 22/50 [00:38<00:49, 1.78s/it] 46%|████▌ | 23/50 [00:40<00:48, 1.78s/it] 48%|████▊ | 24/50 [00:42<00:46, 1.78s/it] 50%|█████ | 25/50 [00:43<00:44, 1.78s/it] 52%|█████▏ | 26/50 [00:45<00:42, 1.78s/it] 54%|█████▍ | 27/50 [00:47<00:40, 1.78s/it] 56%|█████▌ | 28/50 [00:49<00:39, 1.78s/it] 58%|█████▊ | 29/50 [00:51<00:37, 1.78s/it] 60%|██████ | 30/50 [00:52<00:35, 1.78s/it] 62%|██████▏ | 31/50 [00:54<00:33, 1.78s/it] 64%|██████▍ | 32/50 [00:56<00:32, 1.78s/it] 66%|██████▌ | 33/50 [00:58<00:30, 1.78s/it] 68%|██████▊ | 34/50 [01:00<00:28, 1.78s/it] 70%|███████ | 35/50 [01:01<00:26, 1.78s/it] 72%|███████▏ | 36/50 [01:03<00:24, 1.78s/it] 74%|███████▍ | 37/50 [01:05<00:23, 1.78s/it] 76%|███████▌ | 38/50 [01:07<00:21, 1.78s/it] 78%|███████▊ | 39/50 [01:08<00:19, 1.78s/it] 80%|████████ | 40/50 [01:10<00:17, 1.78s/it] 82%|████████▏ | 41/50 [01:12<00:16, 1.78s/it] 84%|████████▍ | 42/50 [01:14<00:14, 1.78s/it] 86%|████████▌ | 43/50 [01:16<00:12, 1.78s/it] 88%|████████▊ | 44/50 [01:17<00:10, 1.78s/it] 90%|█████████ | 45/50 [01:19<00:08, 1.78s/it] 92%|█████████▏| 46/50 [01:21<00:07, 1.78s/it] 94%|█████████▍| 47/50 [01:23<00:05, 1.78s/it] 96%|█████████▌| 48/50 [01:24<00:03, 1.78s/it] 98%|█████████▊| 49/50 [01:26<00:01, 1.78s/it] 100%|██████████| 50/50 [01:28<00:00, 1.78s/it] 100%|██████████| 50/50 [01:28<00:00, 1.77s/it]
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