swk23 / windu
- Public
- 18 runs
-
H100
Prediction
swk23/windu:65f4bf32a31353e76b48659846fba61ecb49445c20a0d365f9a83fd151193847ModelID0za0krys0srm80cn2ktabjavcrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- mask
- image
- model
- dev
- prompt
- windu sitting in a chair
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 21:9
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "mask": "https://replicate.delivery/pbxt/MW3Dyqdtn6JdKvOzr9qFJLdIzmivKKu25vFrWc1cXyJqL2Ru/test.png", "image": "https://replicate.delivery/pbxt/MW3DzDSPvSGGCirpj7SByIOUEHcXJBBLSGvDe1PuUrpaPgbO/full.png", "model": "dev", "prompt": "windu sitting in a chair ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "21:9", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }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 swk23/windu using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "swk23/windu:65f4bf32a31353e76b48659846fba61ecb49445c20a0d365f9a83fd151193847", { input: { mask: "https://replicate.delivery/pbxt/MW3Dyqdtn6JdKvOzr9qFJLdIzmivKKu25vFrWc1cXyJqL2Ru/test.png", image: "https://replicate.delivery/pbxt/MW3DzDSPvSGGCirpj7SByIOUEHcXJBBLSGvDe1PuUrpaPgbO/full.png", model: "dev", prompt: "windu sitting in a chair ", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "21:9", output_format: "jpg", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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 swk23/windu using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "swk23/windu:65f4bf32a31353e76b48659846fba61ecb49445c20a0d365f9a83fd151193847", input={ "mask": "https://replicate.delivery/pbxt/MW3Dyqdtn6JdKvOzr9qFJLdIzmivKKu25vFrWc1cXyJqL2Ru/test.png", "image": "https://replicate.delivery/pbxt/MW3DzDSPvSGGCirpj7SByIOUEHcXJBBLSGvDe1PuUrpaPgbO/full.png", "model": "dev", "prompt": "windu sitting in a chair ", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "21:9", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run swk23/windu 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": "swk23/windu:65f4bf32a31353e76b48659846fba61ecb49445c20a0d365f9a83fd151193847", "input": { "mask": "https://replicate.delivery/pbxt/MW3Dyqdtn6JdKvOzr9qFJLdIzmivKKu25vFrWc1cXyJqL2Ru/test.png", "image": "https://replicate.delivery/pbxt/MW3DzDSPvSGGCirpj7SByIOUEHcXJBBLSGvDe1PuUrpaPgbO/full.png", "model": "dev", "prompt": "windu sitting in a chair ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "21:9", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/swk23/windu@sha256:65f4bf32a31353e76b48659846fba61ecb49445c20a0d365f9a83fd151193847 \ -i 'mask="https://replicate.delivery/pbxt/MW3Dyqdtn6JdKvOzr9qFJLdIzmivKKu25vFrWc1cXyJqL2Ru/test.png"' \ -i 'image="https://replicate.delivery/pbxt/MW3DzDSPvSGGCirpj7SByIOUEHcXJBBLSGvDe1PuUrpaPgbO/full.png"' \ -i 'model="dev"' \ -i 'prompt="windu sitting in a chair "' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="21:9"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/swk23/windu@sha256:65f4bf32a31353e76b48659846fba61ecb49445c20a0d365f9a83fd151193847curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "mask": "https://replicate.delivery/pbxt/MW3Dyqdtn6JdKvOzr9qFJLdIzmivKKu25vFrWc1cXyJqL2Ru/test.png", "image": "https://replicate.delivery/pbxt/MW3DzDSPvSGGCirpj7SByIOUEHcXJBBLSGvDe1PuUrpaPgbO/full.png", "model": "dev", "prompt": "windu sitting in a chair ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "21:9", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-02-17T17:29:18.098190Z", "created_at": "2025-02-17T17:29:05.542000Z", "data_removed": false, "error": null, "id": "0za0krys0srm80cn2ktabjavcr", "input": { "mask": "https://replicate.delivery/pbxt/MW3Dyqdtn6JdKvOzr9qFJLdIzmivKKu25vFrWc1cXyJqL2Ru/test.png", "image": "https://replicate.delivery/pbxt/MW3DzDSPvSGGCirpj7SByIOUEHcXJBBLSGvDe1PuUrpaPgbO/full.png", "model": "dev", "prompt": "windu sitting in a chair ", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "21:9", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=28122040393728\nDownloading weights\n2025-02-17T17:29:09Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpxb71_ofw/weights url=https://replicate.delivery/xezq/elmrBIPtlCyRYaRsePplNWBGJOrcq6QlPv2pAFje42I50xynA/trained_model.tar\n2025-02-17T17:29:11Z | INFO | [ Complete ] dest=/tmp/tmpxb71_ofw/weights size=\"172 MB\" total_elapsed=1.324s url=https://replicate.delivery/xezq/elmrBIPtlCyRYaRsePplNWBGJOrcq6QlPv2pAFje42I50xynA/trained_model.tar\nDownloaded weights in 1.35s\nLoaded LoRAs in 1.90s\nUsing seed: 5644\nPrompt: windu sitting in a chair\nInput image size: 1536x640\n[!] Resizing input image from 1536x640 to 1440x608\n[!] inpaint mode\n 0%| | 0/23 [00:00<?, ?it/s]\n 4%|▍ | 1/23 [00:00<00:19, 1.10it/s]\n 9%|▊ | 2/23 [00:01<00:10, 2.01it/s]\n 13%|█▎ | 3/23 [00:01<00:07, 2.71it/s]\n 17%|█▋ | 4/23 [00:01<00:05, 3.25it/s]\n 22%|██▏ | 5/23 [00:01<00:04, 3.66it/s]\n 26%|██▌ | 6/23 [00:01<00:04, 3.95it/s]\n 30%|███ | 7/23 [00:02<00:03, 4.17it/s]\n 35%|███▍ | 8/23 [00:02<00:03, 4.32it/s]\n 39%|███▉ | 9/23 [00:02<00:03, 4.43it/s]\n 43%|████▎ | 10/23 [00:02<00:02, 4.51it/s]\n 48%|████▊ | 11/23 [00:03<00:02, 4.56it/s]\n 52%|█████▏ | 12/23 [00:03<00:02, 4.60it/s]\n 57%|█████▋ | 13/23 [00:03<00:02, 4.62it/s]\n 61%|██████ | 14/23 [00:03<00:01, 4.64it/s]\n 65%|██████▌ | 15/23 [00:03<00:01, 4.66it/s]\n 70%|██████▉ | 16/23 [00:04<00:01, 4.67it/s]\n 74%|███████▍ | 17/23 [00:04<00:01, 4.67it/s]\n 78%|███████▊ | 18/23 [00:04<00:01, 4.68it/s]\n 83%|████████▎ | 19/23 [00:04<00:00, 4.68it/s]\n 87%|████████▋ | 20/23 [00:04<00:00, 4.68it/s]\n 91%|█████████▏| 21/23 [00:05<00:00, 4.66it/s]\n 96%|█████████▌| 22/23 [00:05<00:00, 4.67it/s]\n100%|██████████| 23/23 [00:05<00:00, 4.95it/s]\n100%|██████████| 23/23 [00:05<00:00, 4.13it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.681173174, "total_time": 12.55619 }, "output": [ "https://replicate.delivery/xezq/NKc9yAJafxSf50I4hqASrl83NcSqxTRDmD1oeQI6TGRdfIBRB/out-0.jpg" ], "started_at": "2025-02-17T17:29:09.417017Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-nsrnjhks7kabyl7wgzyz5zqimyefejh6pkiajvcluqx24h3ccaqa", "get": "https://api.replicate.com/v1/predictions/0za0krys0srm80cn2ktabjavcr", "cancel": "https://api.replicate.com/v1/predictions/0za0krys0srm80cn2ktabjavcr/cancel" }, "version": "65f4bf32a31353e76b48659846fba61ecb49445c20a0d365f9a83fd151193847" }Generated infree=28122040393728 Downloading weights 2025-02-17T17:29:09Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpxb71_ofw/weights url=https://replicate.delivery/xezq/elmrBIPtlCyRYaRsePplNWBGJOrcq6QlPv2pAFje42I50xynA/trained_model.tar 2025-02-17T17:29:11Z | INFO | [ Complete ] dest=/tmp/tmpxb71_ofw/weights size="172 MB" total_elapsed=1.324s url=https://replicate.delivery/xezq/elmrBIPtlCyRYaRsePplNWBGJOrcq6QlPv2pAFje42I50xynA/trained_model.tar Downloaded weights in 1.35s Loaded LoRAs in 1.90s Using seed: 5644 Prompt: windu sitting in a chair Input image size: 1536x640 [!] Resizing input image from 1536x640 to 1440x608 [!] inpaint mode 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:19, 1.10it/s] 9%|▊ | 2/23 [00:01<00:10, 2.01it/s] 13%|█▎ | 3/23 [00:01<00:07, 2.71it/s] 17%|█▋ | 4/23 [00:01<00:05, 3.25it/s] 22%|██▏ | 5/23 [00:01<00:04, 3.66it/s] 26%|██▌ | 6/23 [00:01<00:04, 3.95it/s] 30%|███ | 7/23 [00:02<00:03, 4.17it/s] 35%|███▍ | 8/23 [00:02<00:03, 4.32it/s] 39%|███▉ | 9/23 [00:02<00:03, 4.43it/s] 43%|████▎ | 10/23 [00:02<00:02, 4.51it/s] 48%|████▊ | 11/23 [00:03<00:02, 4.56it/s] 52%|█████▏ | 12/23 [00:03<00:02, 4.60it/s] 57%|█████▋ | 13/23 [00:03<00:02, 4.62it/s] 61%|██████ | 14/23 [00:03<00:01, 4.64it/s] 65%|██████▌ | 15/23 [00:03<00:01, 4.66it/s] 70%|██████▉ | 16/23 [00:04<00:01, 4.67it/s] 74%|███████▍ | 17/23 [00:04<00:01, 4.67it/s] 78%|███████▊ | 18/23 [00:04<00:01, 4.68it/s] 83%|████████▎ | 19/23 [00:04<00:00, 4.68it/s] 87%|████████▋ | 20/23 [00:04<00:00, 4.68it/s] 91%|█████████▏| 21/23 [00:05<00:00, 4.66it/s] 96%|█████████▌| 22/23 [00:05<00:00, 4.67it/s] 100%|██████████| 23/23 [00:05<00:00, 4.95it/s] 100%|██████████| 23/23 [00:05<00:00, 4.13it/s] Total safe images: 1 out of 1
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