juddisjudd
/
deriksen
- Public
- 20 runs
-
H100
Prediction
juddisjudd/deriksen:b7866b7dIDpefpet5nvnrm20chpeg92gggpgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- width
- 702
- height
- 842
- prompt
- a photo of deriksen in a black and gold suit standing in a pawn shop canon eos 7d, realistic, 35mm
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- png
- guidance_scale
- 3.5
- output_quality
- 100
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "width": 702, "height": 842, "prompt": "a photo of deriksen in a black and gold suit standing in a pawn shop canon eos 7d, realistic, 35mm", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }npm install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run juddisjudd/deriksen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "juddisjudd/deriksen:b7866b7d216effe38b0f969b4b587040b4ebd2f22a32c6d4f3e1b45b5c1bb1c4", { input: { model: "dev", width: 702, height: 842, prompt: "a photo of deriksen in a black and gold suit standing in a pawn shop canon eos 7d, realistic, 35mm", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "png", guidance_scale: 3.5, output_quality: 100, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the clientimport replicateRun juddisjudd/deriksen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "juddisjudd/deriksen:b7866b7d216effe38b0f969b4b587040b4ebd2f22a32c6d4f3e1b45b5c1bb1c4", input={ "model": "dev", "width": 702, "height": 842, "prompt": "a photo of deriksen in a black and gold suit standing in a pawn shop canon eos 7d, realistic, 35mm", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run juddisjudd/deriksen 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": "b7866b7d216effe38b0f969b4b587040b4ebd2f22a32c6d4f3e1b45b5c1bb1c4", "input": { "model": "dev", "width": 702, "height": 842, "prompt": "a photo of deriksen in a black and gold suit standing in a pawn shop canon eos 7d, realistic, 35mm", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-02T16:46:22.335104Z", "created_at": "2024-09-02T16:45:39.677000Z", "data_removed": false, "error": null, "id": "pefpet5nvnrm20chpeg92gggpg", "input": { "model": "dev", "width": 702, "height": 842, "prompt": "a photo of deriksen in a black and gold suit standing in a pawn shop canon eos 7d, realistic, 35mm", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3.5, "output_quality": 100, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 39543\nPrompt: a photo of deriksen in a black and gold suit standing in a pawn shop canon eos 7d, realistic, 35mm\ntxt2img mode\nUsing dev model\nfree=9589539794944\nDownloading weights\n2024-09-02T16:45:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp4xgljv2s/weights url=https://replicate.delivery/yhqm/QudUfySKoHTjZyBe161DKPft2GAixRHFsRLcc8txc01eSnjNB/trained_model.tar\n2024-09-02T16:45:41Z | INFO | [ Complete ] dest=/tmp/tmp4xgljv2s/weights size=\"172 MB\" total_elapsed=1.575s url=https://replicate.delivery/yhqm/QudUfySKoHTjZyBe161DKPft2GAixRHFsRLcc8txc01eSnjNB/trained_model.tar\nDownloaded weights in 1.61s\nLoaded LoRAs in 10.78s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:27, 1.02s/it]\n 7%|▋ | 2/28 [00:01<00:23, 1.12it/s]\n 11%|█ | 3/28 [00:02<00:23, 1.05it/s]\n 14%|█▍ | 4/28 [00:03<00:23, 1.02it/s]\n 18%|█▊ | 5/28 [00:04<00:22, 1.00it/s]\n 21%|██▏ | 6/28 [00:05<00:22, 1.01s/it]\n 25%|██▌ | 7/28 [00:06<00:21, 1.01s/it]\n 29%|██▊ | 8/28 [00:07<00:20, 1.02s/it]\n 32%|███▏ | 9/28 [00:09<00:19, 1.02s/it]\n 36%|███▌ | 10/28 [00:10<00:18, 1.02s/it]\n 39%|███▉ | 11/28 [00:11<00:17, 1.02s/it]\n 43%|████▎ | 12/28 [00:12<00:16, 1.03s/it]\n 46%|████▋ | 13/28 [00:13<00:15, 1.03s/it]\n 50%|█████ | 14/28 [00:14<00:14, 1.03s/it]\n 54%|█████▎ | 15/28 [00:15<00:13, 1.03s/it]\n 57%|█████▋ | 16/28 [00:16<00:12, 1.03s/it]\n 61%|██████ | 17/28 [00:17<00:11, 1.03s/it]\n 64%|██████▍ | 18/28 [00:18<00:10, 1.03s/it]\n 68%|██████▊ | 19/28 [00:19<00:09, 1.03s/it]\n 71%|███████▏ | 20/28 [00:20<00:08, 1.03s/it]\n 75%|███████▌ | 21/28 [00:21<00:07, 1.03s/it]\n 79%|███████▊ | 22/28 [00:22<00:06, 1.03s/it]\n 82%|████████▏ | 23/28 [00:23<00:05, 1.03s/it]\n 86%|████████▌ | 24/28 [00:24<00:04, 1.03s/it]\n 89%|████████▉ | 25/28 [00:25<00:03, 1.03s/it]\n 93%|█████████▎| 26/28 [00:26<00:02, 1.03s/it]\n 96%|█████████▋| 27/28 [00:27<00:01, 1.03s/it]\n100%|██████████| 28/28 [00:28<00:00, 1.03s/it]\n100%|██████████| 28/28 [00:28<00:00, 1.02s/it]", "metrics": { "predict_time": 42.649322154000004, "total_time": 42.658104 }, "output": [ "https://replicate.delivery/yhqm/5wUS5QWJHmKLDFYP86faZehULMeTLDjDeLqHHINReXMt7OHbC/out-0.png", "https://replicate.delivery/yhqm/tYSQJJw4XMbAA939zyW4bzAx2rQUgv0hAcwonPiNlBa3dO2E/out-1.png", "https://replicate.delivery/yhqm/rC5gqCf2aep4v0ooNPBD0hM6i0HilJYdjEipkXgeNNX8uzxmA/out-2.png", "https://replicate.delivery/yhqm/RAJhuiJQbgbrOlPRelDNKFeU6qeLWQVY03giCeTeRGO07OHbC/out-3.png" ], "started_at": "2024-09-02T16:45:39.685782Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/pefpet5nvnrm20chpeg92gggpg", "cancel": "https://api.replicate.com/v1/predictions/pefpet5nvnrm20chpeg92gggpg/cancel" }, "version": "b7866b7d216effe38b0f969b4b587040b4ebd2f22a32c6d4f3e1b45b5c1bb1c4" }Generated inUsing seed: 39543 Prompt: a photo of deriksen in a black and gold suit standing in a pawn shop canon eos 7d, realistic, 35mm txt2img mode Using dev model free=9589539794944 Downloading weights 2024-09-02T16:45:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp4xgljv2s/weights url=https://replicate.delivery/yhqm/QudUfySKoHTjZyBe161DKPft2GAixRHFsRLcc8txc01eSnjNB/trained_model.tar 2024-09-02T16:45:41Z | INFO | [ Complete ] dest=/tmp/tmp4xgljv2s/weights size="172 MB" total_elapsed=1.575s url=https://replicate.delivery/yhqm/QudUfySKoHTjZyBe161DKPft2GAixRHFsRLcc8txc01eSnjNB/trained_model.tar Downloaded weights in 1.61s Loaded LoRAs in 10.78s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:27, 1.02s/it] 7%|▋ | 2/28 [00:01<00:23, 1.12it/s] 11%|█ | 3/28 [00:02<00:23, 1.05it/s] 14%|█▍ | 4/28 [00:03<00:23, 1.02it/s] 18%|█▊ | 5/28 [00:04<00:22, 1.00it/s] 21%|██▏ | 6/28 [00:05<00:22, 1.01s/it] 25%|██▌ | 7/28 [00:06<00:21, 1.01s/it] 29%|██▊ | 8/28 [00:07<00:20, 1.02s/it] 32%|███▏ | 9/28 [00:09<00:19, 1.02s/it] 36%|███▌ | 10/28 [00:10<00:18, 1.02s/it] 39%|███▉ | 11/28 [00:11<00:17, 1.02s/it] 43%|████▎ | 12/28 [00:12<00:16, 1.03s/it] 46%|████▋ | 13/28 [00:13<00:15, 1.03s/it] 50%|█████ | 14/28 [00:14<00:14, 1.03s/it] 54%|█████▎ | 15/28 [00:15<00:13, 1.03s/it] 57%|█████▋ | 16/28 [00:16<00:12, 1.03s/it] 61%|██████ | 17/28 [00:17<00:11, 1.03s/it] 64%|██████▍ | 18/28 [00:18<00:10, 1.03s/it] 68%|██████▊ | 19/28 [00:19<00:09, 1.03s/it] 71%|███████▏ | 20/28 [00:20<00:08, 1.03s/it] 75%|███████▌ | 21/28 [00:21<00:07, 1.03s/it] 79%|███████▊ | 22/28 [00:22<00:06, 1.03s/it] 82%|████████▏ | 23/28 [00:23<00:05, 1.03s/it] 86%|████████▌ | 24/28 [00:24<00:04, 1.03s/it] 89%|████████▉ | 25/28 [00:25<00:03, 1.03s/it] 93%|█████████▎| 26/28 [00:26<00:02, 1.03s/it] 96%|█████████▋| 27/28 [00:27<00:01, 1.03s/it] 100%|██████████| 28/28 [00:28<00:00, 1.03s/it] 100%|██████████| 28/28 [00:28<00:00, 1.02s/it]
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