Prediction

Model

zylim0702/sdxl-lora-customize-model:5a2b1cff

2ygygulbup6s4ynexsp2n5c3ua

Status

Succeeded

Source

Web

Hardware

A40

Total duration

35.9s

Created

over 2 years ago by zylim0702

Webhook

–

Input

Lora_url: https://replicate.delivery/pbxt/aEt6InPOlTpZJZ9Y1664pLuWBf5ZdIKdjDK4FmHVB2EA47tIA/trained_model.tar
prompt: a photo of TOK , white background, pink blazer, american hairstyle
width: 1024
height: 1024
num_outputs: 4
scheduler: K_EULER
num_inference_steps: 20
guidance_scale: 7.5
prompt_strength: 0.8
refine: no_refiner
high_noise_frac: 0.8
apply_watermark: true
lora_scale: 0.6

{
  "Lora_url": "https://replicate.delivery/pbxt/aEt6InPOlTpZJZ9Y1664pLuWBf5ZdIKdjDK4FmHVB2EA47tIA/trained_model.tar",
  "apply_watermark": true,
  "guidance_scale": 7.5,
  "height": 1024,
  "high_noise_frac": 0.8,
  "lora_scale": 0.6,
  "num_inference_steps": 20,
  "num_outputs": 4,
  "prompt": "a photo of TOK , white background, pink blazer, american hairstyle",
  "prompt_strength": 0.8,
  "refine": "no_refiner",
  "scheduler": "K_EULER",
  "width": 1024
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_20N**********************************

This is your API token. Keep it to yourself.

Import 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 zylim0702/sdxl-lora-customize-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "zylim0702/sdxl-lora-customize-model:5a2b1cff79a2cf60d2a498b424795a90e26b7a3992fbd13b340f73ff4942b81e",
  {
    input: {
      Lora_url: "https://replicate.delivery/pbxt/aEt6InPOlTpZJZ9Y1664pLuWBf5ZdIKdjDK4FmHVB2EA47tIA/trained_model.tar",
      apply_watermark: true,
      guidance_scale: 7.5,
      height: 1024,
      high_noise_frac: 0.8,
      lora_scale: 0.6,
      num_inference_steps: 20,
      num_outputs: 4,
      prompt: "a photo of TOK , white background, pink blazer, american hairstyle",
      prompt_strength: 0.8,
      refine: "no_refiner",
      scheduler: "K_EULER",
      width: 1024
    }
  }
);

// 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 replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_20N**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run zylim0702/sdxl-lora-customize-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "zylim0702/sdxl-lora-customize-model:5a2b1cff79a2cf60d2a498b424795a90e26b7a3992fbd13b340f73ff4942b81e",
    input={
        "Lora_url": "https://replicate.delivery/pbxt/aEt6InPOlTpZJZ9Y1664pLuWBf5ZdIKdjDK4FmHVB2EA47tIA/trained_model.tar",
        "apply_watermark": True,
        "guidance_scale": 7.5,
        "height": 1024,
        "high_noise_frac": 0.8,
        "lora_scale": 0.6,
        "num_inference_steps": 20,
        "num_outputs": 4,
        "prompt": "a photo of TOK , white background, pink blazer, american hairstyle",
        "prompt_strength": 0.8,
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "width": 1024
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_20N**********************************

This is your API token. Keep it to yourself.

Run zylim0702/sdxl-lora-customize-model 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": "zylim0702/sdxl-lora-customize-model:5a2b1cff79a2cf60d2a498b424795a90e26b7a3992fbd13b340f73ff4942b81e",
    "input": {
      "Lora_url": "https://replicate.delivery/pbxt/aEt6InPOlTpZJZ9Y1664pLuWBf5ZdIKdjDK4FmHVB2EA47tIA/trained_model.tar",
      "apply_watermark": true,
      "guidance_scale": 7.5,
      "height": 1024,
      "high_noise_frac": 0.8,
      "lora_scale": 0.6,
      "num_inference_steps": 20,
      "num_outputs": 4,
      "prompt": "a photo of TOK , white background, pink blazer, american hairstyle",
      "prompt_strength": 0.8,
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "width": 1024
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "id": "2ygygulbup6s4ynexsp2n5c3ua",
  "model": "zylim0702/sdxl-lora-customize-model",
  "version": "5a2b1cff79a2cf60d2a498b424795a90e26b7a3992fbd13b340f73ff4942b81e",
  "input": {
    "Lora_url": "https://replicate.delivery/pbxt/aEt6InPOlTpZJZ9Y1664pLuWBf5ZdIKdjDK4FmHVB2EA47tIA/trained_model.tar",
    "apply_watermark": true,
    "guidance_scale": 7.5,
    "height": 1024,
    "high_noise_frac": 0.8,
    "lora_scale": 0.6,
    "num_inference_steps": 20,
    "num_outputs": 4,
    "prompt": "a photo of TOK , white background, pink blazer, american hairstyle",
    "prompt_strength": 0.8,
    "refine": "no_refiner",
    "scheduler": "K_EULER",
    "width": 1024
  },
  "logs": "Loading sdxl txt2img pipeline...\nLoading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]\nLoading pipeline components...:  14%|█▍        | 1/7 [00:00<00:02,  2.77it/s]\nLoading pipeline components...:  29%|██▊       | 2/7 [00:01<00:03,  1.48it/s]\nLoading pipeline components...:  43%|████▎     | 3/7 [00:01<00:02,  1.90it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:01<00:00,  5.68it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:01<00:00,  3.95it/s]\nLoading fine-tuned model\nDoes not have Unet. Assume we are using LoRA\nLoading Unet LoRA\nLoading SDXL img2img pipeline...\nLoading SDXL inpaint pipeline...\nLoading SDXL refiner pipeline...\nLoading refiner pipeline...\nLoading pipeline components...:   0%|          | 0/4 [00:00<?, ?it/s]\nLoading pipeline components...:  25%|██▌       | 1/4 [00:00<00:01,  1.52it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:00<00:00,  5.71it/s]\nUsing seed: 8931\nPrompt: a photo of <s0><s1> , white background, pink blazer, american hairstyle\ntxt2img mode\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:18,  1.00it/s]\n 10%|█         | 2/20 [00:01<00:17,  1.00it/s]\n 15%|█▌        | 3/20 [00:02<00:16,  1.00it/s]\n 20%|██        | 4/20 [00:03<00:15,  1.00it/s]\n 25%|██▌       | 5/20 [00:04<00:14,  1.00it/s]\n 30%|███       | 6/20 [00:05<00:13,  1.00it/s]\n 35%|███▌      | 7/20 [00:06<00:12,  1.00it/s]\n 40%|████      | 8/20 [00:07<00:12,  1.00s/it]\n 45%|████▌     | 9/20 [00:08<00:11,  1.00s/it]\n 50%|█████     | 10/20 [00:09<00:09,  1.00it/s]\n 55%|█████▌    | 11/20 [00:10<00:08,  1.00it/s]\n 60%|██████    | 12/20 [00:11<00:07,  1.00it/s]\n 65%|██████▌   | 13/20 [00:12<00:06,  1.00it/s]\n 70%|███████   | 14/20 [00:13<00:05,  1.00it/s]\n 75%|███████▌  | 15/20 [00:14<00:04,  1.00it/s]\n 80%|████████  | 16/20 [00:15<00:03,  1.00it/s]\n 85%|████████▌ | 17/20 [00:16<00:02,  1.00it/s]\n 90%|█████████ | 18/20 [00:17<00:01,  1.00it/s]\n 95%|█████████▌| 19/20 [00:18<00:01,  1.00s/it]\n100%|██████████| 20/20 [00:19<00:00,  1.00s/it]\n100%|██████████| 20/20 [00:19<00:00,  1.00it/s]",
  "output": [
    "https://replicate.delivery/pbxt/Zk65CFgBb5IFJVh3wHmocSMGbgZ1jLIvTeeo8b31B3ph03bRA/out-0.png",
    "https://replicate.delivery/pbxt/cHq7PLwgkWb8LlFYXOepVna3PY5dfhbeJQQcMxXfdfrXke9WE/out-1.png",
    "https://replicate.delivery/pbxt/1qSkUORcadLnEJDxNPtLXdnCMBkEp9jmDxKyGIR9mOuI99WE/out-2.png",
    "https://replicate.delivery/pbxt/nSoKenfp8aqFTkQ4qcDeifAOKbPXeRarzT6fj3I1cm6zI99WE/out-3.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-08-20T08:12:47.927861Z",
  "started_at": "2023-08-20T08:12:47.935968Z",
  "completed_at": "2023-08-20T08:13:23.776805Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/2ygygulbup6s4ynexsp2n5c3ua/cancel",
    "get": "https://api.replicate.com/v1/predictions/2ygygulbup6s4ynexsp2n5c3ua"
  },
  "metrics": {
    "predict_time": 35.840837,
    "total_time": 35.848944
  }
}

Generated in

35.9 seconds

Tweak it Report

Loading sdxl txt2img pipeline... Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s] Loading pipeline components...: 14%|█▍ | 1/7 [00:00<00:02, 2.77it/s] Loading pipeline components...: 29%|██▊ | 2/7 [00:01<00:03, 1.48it/s] Loading pipeline components...: 43%|████▎ | 3/7 [00:01<00:02, 1.90it/s] Loading pipeline components...: 100%|██████████| 7/7 [00:01<00:00, 5.68it/s] Loading pipeline components...: 100%|██████████| 7/7 [00:01<00:00, 3.95it/s] Loading fine-tuned model Does not have Unet. Assume we are using LoRA Loading Unet LoRA Loading SDXL img2img pipeline... Loading SDXL inpaint pipeline... Loading SDXL refiner pipeline... Loading refiner pipeline... Loading pipeline components...: 0%| | 0/4 [00:00<?, ?it/s] Loading pipeline components...: 25%|██▌ | 1/4 [00:00<00:01, 1.52it/s] Loading pipeline components...: 100%|██████████| 4/4 [00:00<00:00, 5.71it/s] Using seed: 8931 Prompt: a photo of <s0><s1> , white background, pink blazer, american hairstyle txt2img mode 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:18, 1.00it/s] 10%|█ | 2/20 [00:01<00:17, 1.00it/s] 15%|█▌ | 3/20 [00:02<00:16, 1.00it/s] 20%|██ | 4/20 [00:03<00:15, 1.00it/s] 25%|██▌ | 5/20 [00:04<00:14, 1.00it/s] 30%|███ | 6/20 [00:05<00:13, 1.00it/s] 35%|███▌ | 7/20 [00:06<00:12, 1.00it/s] 40%|████ | 8/20 [00:07<00:12, 1.00s/it] 45%|████▌ | 9/20 [00:08<00:11, 1.00s/it] 50%|█████ | 10/20 [00:09<00:09, 1.00it/s] 55%|█████▌ | 11/20 [00:10<00:08, 1.00it/s] 60%|██████ | 12/20 [00:11<00:07, 1.00it/s] 65%|██████▌ | 13/20 [00:12<00:06, 1.00it/s] 70%|███████ | 14/20 [00:13<00:05, 1.00it/s] 75%|███████▌ | 15/20 [00:14<00:04, 1.00it/s] 80%|████████ | 16/20 [00:15<00:03, 1.00it/s] 85%|████████▌ | 17/20 [00:16<00:02, 1.00it/s] 90%|█████████ | 18/20 [00:17<00:01, 1.00it/s] 95%|█████████▌| 19/20 [00:18<00:01, 1.00s/it] 100%|██████████| 20/20 [00:19<00:00, 1.00s/it] 100%|██████████| 20/20 [00:19<00:00, 1.00it/s]