Prediction

Model

lucataco/sdxl:c86579ac

4q90w8cqpsrme0ckkq88t6023m

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

3.6s

Created

about 1 year ago

Webhook

–

Input

prompt: a studio portrait photo of an iguana wearing a hat
negative_prompt: Empty string
width: 1024
height: 1024
num_outputs: 1
scheduler: DDIM
num_inference_steps: 25
guidance_scale: 7.5
prompt_strength: 0.8
seed: 39287
refine: expert_ensemble_refiner
high_noise_frac: 0.8
apply_watermark: true
lora_scale: 0.6

{
  "apply_watermark": true,
  "guidance_scale": 7.5,
  "height": 1024,
  "high_noise_frac": 0.8,
  "lora_scale": 0.6,
  "negative_prompt": "",
  "num_inference_steps": 25,
  "num_outputs": 1,
  "prompt": "a studio portrait photo of an iguana wearing a hat",
  "prompt_strength": 0.8,
  "refine": "expert_ensemble_refiner",
  "scheduler": "DDIM",
  "seed": 39287,
  "width": 1024
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_HWW**********************************

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 lucataco/sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/sdxl:c86579ac5193bf45422f1c8b92742135aa859b1850a8e4c531bff222fc75273d",
  {
    input: {
      apply_watermark: true,
      guidance_scale: 7.5,
      height: 1024,
      high_noise_frac: 0.8,
      lora_scale: 0.6,
      negative_prompt: "",
      num_inference_steps: 25,
      num_outputs: 1,
      prompt: "a studio portrait photo of an iguana wearing a hat",
      prompt_strength: 0.8,
      refine: "expert_ensemble_refiner",
      scheduler: "DDIM",
      seed: 39287,
      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_HWW**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/sdxl:c86579ac5193bf45422f1c8b92742135aa859b1850a8e4c531bff222fc75273d",
    input={
        "apply_watermark": True,
        "guidance_scale": 7.5,
        "height": 1024,
        "high_noise_frac": 0.8,
        "lora_scale": 0.6,
        "negative_prompt": "",
        "num_inference_steps": 25,
        "num_outputs": 1,
        "prompt": "a studio portrait photo of an iguana wearing a hat",
        "prompt_strength": 0.8,
        "refine": "expert_ensemble_refiner",
        "scheduler": "DDIM",
        "seed": 39287,
        "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_HWW**********************************

This is your API token. Keep it to yourself.

Run lucataco/sdxl 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": "lucataco/sdxl:c86579ac5193bf45422f1c8b92742135aa859b1850a8e4c531bff222fc75273d",
    "input": {
      "apply_watermark": true,
      "guidance_scale": 7.5,
      "height": 1024,
      "high_noise_frac": 0.8,
      "lora_scale": 0.6,
      "negative_prompt": "",
      "num_inference_steps": 25,
      "num_outputs": 1,
      "prompt": "a studio portrait photo of an iguana wearing a hat",
      "prompt_strength": 0.8,
      "refine": "expert_ensemble_refiner",
      "scheduler": "DDIM",
      "seed": 39287,
      "width": 1024
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "4q90w8cqpsrme0ckkq88t6023m",
  "model": "lucataco/sdxl",
  "version": "c86579ac5193bf45422f1c8b92742135aa859b1850a8e4c531bff222fc75273d",
  "input": {
    "apply_watermark": true,
    "guidance_scale": 7.5,
    "height": 1024,
    "high_noise_frac": 0.8,
    "lora_scale": 0.6,
    "negative_prompt": "",
    "num_inference_steps": 25,
    "num_outputs": 1,
    "prompt": "a studio portrait photo of an iguana wearing a hat",
    "prompt_strength": 0.8,
    "refine": "expert_ensemble_refiner",
    "scheduler": "DDIM",
    "seed": 39287,
    "width": 1024
  },
  "logs": "Using seed: 39287\nPrompt: a studio portrait photo of an iguana wearing a hat\ntxt2img mode\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:02,  9.39it/s]\n 10%|█         | 2/20 [00:00<00:01,  9.18it/s]\n 15%|█▌        | 3/20 [00:00<00:01,  9.12it/s]\n 20%|██        | 4/20 [00:00<00:01,  9.09it/s]\n 25%|██▌       | 5/20 [00:00<00:01,  9.08it/s]\n 30%|███       | 6/20 [00:00<00:01,  9.05it/s]\n 35%|███▌      | 7/20 [00:00<00:01,  9.07it/s]\n 40%|████      | 8/20 [00:00<00:01,  9.03it/s]\n 45%|████▌     | 9/20 [00:00<00:01,  9.04it/s]\n 50%|█████     | 10/20 [00:01<00:01,  9.03it/s]\n 55%|█████▌    | 11/20 [00:01<00:00,  9.02it/s]\n 60%|██████    | 12/20 [00:01<00:00,  9.02it/s]\n 65%|██████▌   | 13/20 [00:01<00:00,  9.01it/s]\n 70%|███████   | 14/20 [00:01<00:00,  9.01it/s]\n 75%|███████▌  | 15/20 [00:01<00:00,  9.00it/s]\n 80%|████████  | 16/20 [00:01<00:00,  9.01it/s]\n 85%|████████▌ | 17/20 [00:01<00:00,  9.01it/s]\n 90%|█████████ | 18/20 [00:01<00:00,  9.01it/s]\n 95%|█████████▌| 19/20 [00:02<00:00,  9.00it/s]\n100%|██████████| 20/20 [00:02<00:00,  9.00it/s]\n100%|██████████| 20/20 [00:02<00:00,  9.03it/s]\n  0%|          | 0/5 [00:00<?, ?it/s]\n 20%|██        | 1/5 [00:00<00:00,  8.61it/s]\n 40%|████      | 2/5 [00:00<00:00,  8.40it/s]\n 60%|██████    | 3/5 [00:00<00:00,  8.36it/s]\n 80%|████████  | 4/5 [00:00<00:00,  8.33it/s]\n100%|██████████| 5/5 [00:00<00:00,  8.32it/s]\n100%|██████████| 5/5 [00:00<00:00,  8.35it/s]",
  "output": [
    "https://replicate.delivery/xezq/blqwOdw3lOrYN9edH14RaE1wl2uZgEZkcNAFdnDO099O1I8JA/out-0.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-12-06T21:11:53.526Z",
  "started_at": "2024-12-06T21:11:53.534342Z",
  "completed_at": "2024-12-06T21:11:57.143658Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/4q90w8cqpsrme0ckkq88t6023m/cancel",
    "get": "https://api.replicate.com/v1/predictions/4q90w8cqpsrme0ckkq88t6023m",
    "stream": "https://stream.replicate.com/v1/files/bcwr-gjbs4ohqn5mlazlimuycfnaifps77gscakfh2y47cfgryugixdsq",
    "web": "https://replicate.com/p/4q90w8cqpsrme0ckkq88t6023m"
  },
  "metrics": {
    "predict_time": 3.609316057,
    "total_time": 3.617658
  }
}

Generated in

3.6 seconds

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