Prediction

fv1mkt04zdrm40chr1k8qzd21g

Status

Succeeded

Source

Web

Hardware

H100

Total duration

19.3s

Created

8 months ago

Input

model: dev
prompt: portrait photo of VLTA with purple hair as a charismatic female speaker at conference, captured mid-speech on stage. She is wearing business casual clothes. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text "Replicate"
lora_scale: 1
num_outputs: 1
aspect_ratio: 3:4
output_format: webp
guidance_scale: 3.5
output_quality: 90
prompt_strength: 0.8
extra_lora_scale: 1
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "portrait photo of VLTA with purple hair as a charismatic female speaker at conference, captured mid-speech on stage. She is wearing business casual clothes. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\"",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "3:4",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 90,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

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

const output = await replicate.run(
  "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
  {
    input: {
      model: "dev",
      prompt: "portrait photo of VLTA with purple hair as a charismatic female speaker at conference, captured mid-speech on stage. She is wearing business casual clothes. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\"",
      lora_scale: 1,
      num_outputs: 1,
      aspect_ratio: "3:4",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 90,
      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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    input={
        "model": "dev",
        "prompt": "portrait photo of VLTA with purple hair as a charismatic female speaker at conference, captured mid-speech on stage. She is wearing business casual clothes. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\"",
        "lora_scale": 1,
        "num_outputs": 1,
        "aspect_ratio": "3:4",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 90,
        "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 lucataco/flux-vlta 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": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    "input": {
      "model": "dev",
      "prompt": "portrait photo of VLTA with purple hair as a charismatic female speaker at conference, captured mid-speech on stage. She is wearing business casual clothes. She\'s also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \\"Replicate\\"",
      "lora_scale": 1,
      "num_outputs": 1,
      "aspect_ratio": "3:4",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 90,
      "prompt_strength": 0.8,
      "extra_lora_scale": 1,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-09-05T04:16:56.421570Z",
  "created_at": "2024-09-05T04:16:37.115000Z",
  "data_removed": false,
  "error": null,
  "id": "fv1mkt04zdrm40chr1k8qzd21g",
  "input": {
    "model": "dev",
    "prompt": "portrait photo of VLTA with purple hair as a charismatic female speaker at conference, captured mid-speech on stage. She is wearing business casual clothes. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\"",
    "lora_scale": 1,
    "num_outputs": 1,
    "aspect_ratio": "3:4",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 90,
    "prompt_strength": 0.8,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 61404\nPrompt: portrait photo of VLTA with purple hair as a charismatic female speaker at conference, captured mid-speech on stage. She is wearing business casual clothes. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text \"Replicate\"\ntxt2img mode\nUsing dev model\nfree=8126079803392\nDownloading weights\n2024-09-05T04:16:37Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpd6uzlb90/weights url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar\n2024-09-05T04:16:40Z | INFO  | [ Complete ] dest=/tmp/tmpd6uzlb90/weights size=\"172 MB\" total_elapsed=2.804s url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar\nDownloaded weights in 2.83s\nLoaded LoRAs in 10.79s\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:07,  3.50it/s]\n  7%|▋         | 2/28 [00:00<00:06,  3.97it/s]\n 11%|█         | 3/28 [00:00<00:06,  3.74it/s]\n 14%|█▍        | 4/28 [00:01<00:06,  3.64it/s]\n 18%|█▊        | 5/28 [00:01<00:06,  3.59it/s]\n 21%|██▏       | 6/28 [00:01<00:06,  3.56it/s]\n 25%|██▌       | 7/28 [00:01<00:05,  3.53it/s]\n 29%|██▊       | 8/28 [00:02<00:05,  3.52it/s]\n 32%|███▏      | 9/28 [00:02<00:05,  3.52it/s]\n 36%|███▌      | 10/28 [00:02<00:05,  3.51it/s]\n 39%|███▉      | 11/28 [00:03<00:04,  3.51it/s]\n 43%|████▎     | 12/28 [00:03<00:04,  3.51it/s]\n 46%|████▋     | 13/28 [00:03<00:04,  3.50it/s]\n 50%|█████     | 14/28 [00:03<00:03,  3.51it/s]\n 54%|█████▎    | 15/28 [00:04<00:03,  3.50it/s]\n 57%|█████▋    | 16/28 [00:04<00:03,  3.50it/s]\n 61%|██████    | 17/28 [00:04<00:03,  3.51it/s]\n 64%|██████▍   | 18/28 [00:05<00:02,  3.50it/s]\n 68%|██████▊   | 19/28 [00:05<00:02,  3.50it/s]\n 71%|███████▏  | 20/28 [00:05<00:02,  3.50it/s]\n 75%|███████▌  | 21/28 [00:05<00:01,  3.50it/s]\n 79%|███████▊  | 22/28 [00:06<00:01,  3.50it/s]\n 82%|████████▏ | 23/28 [00:06<00:01,  3.51it/s]\n 86%|████████▌ | 24/28 [00:06<00:01,  3.51it/s]\n 89%|████████▉ | 25/28 [00:07<00:00,  3.50it/s]\n 93%|█████████▎| 26/28 [00:07<00:00,  3.51it/s]\n 96%|█████████▋| 27/28 [00:07<00:00,  3.50it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.50it/s]\n100%|██████████| 28/28 [00:07<00:00,  3.53it/s]",
  "metrics": {
    "predict_time": 19.296487631,
    "total_time": 19.30657
  },
  "output": [
    "https://replicate.delivery/yhqm/62togKkGFF6PHF7qrae2a6x7lAwKo2VVoAjSiAB7kDccF3sJA/out-0.webp"
  ],
  "started_at": "2024-09-05T04:16:37.125082Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/fv1mkt04zdrm40chr1k8qzd21g",
    "cancel": "https://api.replicate.com/v1/predictions/fv1mkt04zdrm40chr1k8qzd21g/cancel"
  },
  "version": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a"
}

Generated in

19.3 seconds

lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a

Using seed: 61404
Prompt: portrait photo of VLTA with purple hair as a charismatic female speaker at conference, captured mid-speech on stage. She is wearing business casual clothes. She's also wearing a simple black lanyard hanging around her neck. The lanyard badge has the text "Replicate"
txt2img mode
Using dev model
free=8126079803392
Downloading weights
2024-09-05T04:16:37Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpd6uzlb90/weights url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar
2024-09-05T04:16:40Z | INFO  | [ Complete ] dest=/tmp/tmpd6uzlb90/weights size="172 MB" total_elapsed=2.804s url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar
Downloaded weights in 2.83s
Loaded LoRAs in 10.79s
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Prediction

Model

yxthx7tww5rm40chr1ra4gdq14

Status

Succeeded

Source

Web

Hardware

H100

Total duration

9.8s

Created

8 months ago

Input

model: dev
prompt: pnt style Illustration of VLTA with purple hair
extra_lora: https://civitai.com/api/download/models/735262
lora_scale: 0.8
num_outputs: 1
aspect_ratio: 1:1
output_format: webp
guidance_scale: 3.5
output_quality: 90
prompt_strength: 0.8
extra_lora_scale: 0.8
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "pnt style Illustration of VLTA with purple hair",
  "extra_lora": "https://civitai.com/api/download/models/735262",
  "lora_scale": 0.8,
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 90,
  "prompt_strength": 0.8,
  "extra_lora_scale": 0.8,
  "num_inference_steps": 28
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

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

const output = await replicate.run(
  "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
  {
    input: {
      model: "dev",
      prompt: "pnt style Illustration of VLTA with purple hair",
      extra_lora: "https://civitai.com/api/download/models/735262",
      lora_scale: 0.8,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 90,
      prompt_strength: 0.8,
      extra_lora_scale: 0.8,
      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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    input={
        "model": "dev",
        "prompt": "pnt style Illustration of VLTA with purple hair",
        "extra_lora": "https://civitai.com/api/download/models/735262",
        "lora_scale": 0.8,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 90,
        "prompt_strength": 0.8,
        "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.

Run lucataco/flux-vlta 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": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    "input": {
      "model": "dev",
      "prompt": "pnt style Illustration of VLTA with purple hair",
      "extra_lora": "https://civitai.com/api/download/models/735262",
      "lora_scale": 0.8,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 90,
      "prompt_strength": 0.8,
      "extra_lora_scale": 0.8,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-09-05T04:28:04.749454Z",
  "created_at": "2024-09-05T04:27:54.977000Z",
  "data_removed": false,
  "error": null,
  "id": "yxthx7tww5rm40chr1ra4gdq14",
  "input": {
    "model": "dev",
    "prompt": "pnt style Illustration of VLTA with purple hair",
    "extra_lora": "https://civitai.com/api/download/models/735262",
    "lora_scale": 0.8,
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 90,
    "prompt_strength": 0.8,
    "extra_lora_scale": 0.8,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 45620\nPrompt: pnt style Illustration of VLTA with purple hair\ntxt2img mode\nUsing dev model\nLoading extra LoRA weights from: https://civitai.com/api/download/models/735262\nWeights already loaded\nLoaded LoRAs in 0.07s\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:08,  3.05it/s]\n  7%|▋         | 2/28 [00:00<00:07,  3.34it/s]\n 11%|█         | 3/28 [00:00<00:07,  3.20it/s]\n 14%|█▍        | 4/28 [00:01<00:07,  3.14it/s]\n 18%|█▊        | 5/28 [00:01<00:07,  3.11it/s]\n 21%|██▏       | 6/28 [00:01<00:07,  3.09it/s]\n 25%|██▌       | 7/28 [00:02<00:06,  3.08it/s]\n 29%|██▊       | 8/28 [00:02<00:06,  3.07it/s]\n 32%|███▏      | 9/28 [00:02<00:06,  3.07it/s]\n 36%|███▌      | 10/28 [00:03<00:05,  3.06it/s]\n 39%|███▉      | 11/28 [00:03<00:05,  3.06it/s]\n 43%|████▎     | 12/28 [00:03<00:05,  3.06it/s]\n 46%|████▋     | 13/28 [00:04<00:04,  3.06it/s]\n 50%|█████     | 14/28 [00:04<00:04,  3.05it/s]\n 54%|█████▎    | 15/28 [00:04<00:04,  3.05it/s]\n 57%|█████▋    | 16/28 [00:05<00:03,  3.05it/s]\n 61%|██████    | 17/28 [00:05<00:03,  3.05it/s]\n 64%|██████▍   | 18/28 [00:05<00:03,  3.05it/s]\n 68%|██████▊   | 19/28 [00:06<00:02,  3.05it/s]\n 71%|███████▏  | 20/28 [00:06<00:02,  3.05it/s]\n 75%|███████▌  | 21/28 [00:06<00:02,  3.05it/s]\n 79%|███████▊  | 22/28 [00:07<00:01,  3.05it/s]\n 82%|████████▏ | 23/28 [00:07<00:01,  3.05it/s]\n 86%|████████▌ | 24/28 [00:07<00:01,  3.05it/s]\n 89%|████████▉ | 25/28 [00:08<00:00,  3.05it/s]\n 93%|█████████▎| 26/28 [00:08<00:00,  3.05it/s]\n 96%|█████████▋| 27/28 [00:08<00:00,  3.05it/s]\n100%|██████████| 28/28 [00:09<00:00,  3.05it/s]\n100%|██████████| 28/28 [00:09<00:00,  3.07it/s]",
  "metrics": {
    "predict_time": 9.76521584,
    "total_time": 9.772454
  },
  "output": [
    "https://replicate.delivery/yhqm/mK6WJHE4liZFBhbY6eVCnHTxuptMX8SlKJ2Be7YzbfPpqczmA/out-0.webp"
  ],
  "started_at": "2024-09-05T04:27:54.984238Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/yxthx7tww5rm40chr1ra4gdq14",
    "cancel": "https://api.replicate.com/v1/predictions/yxthx7tww5rm40chr1ra4gdq14/cancel"
  },
  "version": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a"
}

Generated in

9.8 seconds

lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a

Using seed: 45620
Prompt: pnt style Illustration of VLTA with purple hair
txt2img mode
Using dev model
Loading extra LoRA weights from: https://civitai.com/api/download/models/735262
Weights already loaded
Loaded LoRAs in 0.07s
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Prediction

Model

1a9s7gw3edrm20chr1w933cn0c

Status

Succeeded

Source

Web

Hardware

H100

Total duration

36.0s

Created

8 months ago

Input

model: dev
prompt: style of 80s cyberpunk, portrait photo of VLTA with purple hair
extra_lora: fofr/flux-80s-cyberpunk
lora_scale: 0.8
num_outputs: 1
aspect_ratio: 1:1
output_format: webp
guidance_scale: 3.5
output_quality: 90
prompt_strength: 0.9
extra_lora_scale: 0.8
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "style of 80s cyberpunk, portrait photo of VLTA with purple hair",
  "extra_lora": "fofr/flux-80s-cyberpunk",
  "lora_scale": 0.8,
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 90,
  "prompt_strength": 0.9,
  "extra_lora_scale": 0.8,
  "num_inference_steps": 28
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

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

const output = await replicate.run(
  "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
  {
    input: {
      model: "dev",
      prompt: "style of 80s cyberpunk, portrait photo of VLTA with purple hair",
      extra_lora: "fofr/flux-80s-cyberpunk",
      lora_scale: 0.8,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 90,
      prompt_strength: 0.9,
      extra_lora_scale: 0.8,
      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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    input={
        "model": "dev",
        "prompt": "style of 80s cyberpunk, portrait photo of VLTA with purple hair",
        "extra_lora": "fofr/flux-80s-cyberpunk",
        "lora_scale": 0.8,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 90,
        "prompt_strength": 0.9,
        "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.

Run lucataco/flux-vlta 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": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    "input": {
      "model": "dev",
      "prompt": "style of 80s cyberpunk, portrait photo of VLTA with purple hair",
      "extra_lora": "fofr/flux-80s-cyberpunk",
      "lora_scale": 0.8,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 90,
      "prompt_strength": 0.9,
      "extra_lora_scale": 0.8,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-09-05T04:37:25.173459Z",
  "created_at": "2024-09-05T04:36:49.139000Z",
  "data_removed": false,
  "error": null,
  "id": "1a9s7gw3edrm20chr1w933cn0c",
  "input": {
    "model": "dev",
    "prompt": "style of 80s cyberpunk, portrait photo of VLTA with purple hair",
    "extra_lora": "fofr/flux-80s-cyberpunk",
    "lora_scale": 0.8,
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 90,
    "prompt_strength": 0.9,
    "extra_lora_scale": 0.8,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 41935\nPrompt: style of 80s cyberpunk, portrait photo of VLTA with purple hair\ntxt2img mode\nUsing dev model\nLoading extra LoRA weights from: fofr/flux-80s-cyberpunk\nLoaded LoRAs in 26.23s\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:08,  3.02it/s]\n  7%|▋         | 2/28 [00:00<00:07,  3.31it/s]\n 11%|█         | 3/28 [00:00<00:07,  3.17it/s]\n 14%|█▍        | 4/28 [00:01<00:07,  3.11it/s]\n 18%|█▊        | 5/28 [00:01<00:07,  3.08it/s]\n 21%|██▏       | 6/28 [00:01<00:07,  3.06it/s]\n 25%|██▌       | 7/28 [00:02<00:06,  3.05it/s]\n 29%|██▊       | 8/28 [00:02<00:06,  3.04it/s]\n 32%|███▏      | 9/28 [00:02<00:06,  3.03it/s]\n 36%|███▌      | 10/28 [00:03<00:05,  3.03it/s]\n 39%|███▉      | 11/28 [00:03<00:05,  3.03it/s]\n 43%|████▎     | 12/28 [00:03<00:05,  3.03it/s]\n 46%|████▋     | 13/28 [00:04<00:04,  3.03it/s]\n 50%|█████     | 14/28 [00:04<00:04,  3.03it/s]\n 54%|█████▎    | 15/28 [00:04<00:04,  3.03it/s]\n 57%|█████▋    | 16/28 [00:05<00:03,  3.02it/s]\n 61%|██████    | 17/28 [00:05<00:03,  3.02it/s]\n 64%|██████▍   | 18/28 [00:05<00:03,  3.02it/s]\n 68%|██████▊   | 19/28 [00:06<00:02,  3.02it/s]\n 71%|███████▏  | 20/28 [00:06<00:02,  3.03it/s]\n 75%|███████▌  | 21/28 [00:06<00:02,  3.03it/s]\n 79%|███████▊  | 22/28 [00:07<00:01,  3.03it/s]\n 82%|████████▏ | 23/28 [00:07<00:01,  3.03it/s]\n 86%|████████▌ | 24/28 [00:07<00:01,  3.03it/s]\n 89%|████████▉ | 25/28 [00:08<00:00,  3.03it/s]\n 93%|█████████▎| 26/28 [00:08<00:00,  3.03it/s]\n 96%|█████████▋| 27/28 [00:08<00:00,  3.03it/s]\n100%|██████████| 28/28 [00:09<00:00,  3.03it/s]\n100%|██████████| 28/28 [00:09<00:00,  3.04it/s]",
  "metrics": {
    "predict_time": 36.02496969,
    "total_time": 36.034459
  },
  "output": [
    "https://replicate.delivery/yhqm/fFd5pZfejRG1LIrFee1c84VfSzHwGshxPf7jqSpjT2H2CP3sJA/out-0.webp"
  ],
  "started_at": "2024-09-05T04:36:49.148490Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/1a9s7gw3edrm20chr1w933cn0c",
    "cancel": "https://api.replicate.com/v1/predictions/1a9s7gw3edrm20chr1w933cn0c/cancel"
  },
  "version": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a"
}

Generated in

36.0 seconds

lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a

Prediction

Model

4cg64vcbt1rm20cje72v097b48

Status

Succeeded

Source

Web

Hardware

H100

Total duration

15.7s

Created

7 months ago by @lucataco

Input

model: dev
prompt: Vibrant Calavera, a portrait photo of VLTA with purple hair wearing a colorful and intricate sugar skull makeup with intricate patterns and designs on her face
extra_lora: https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor
lora_scale: 1
num_outputs: 1
aspect_ratio: 1:1
output_format: webp
guidance_scale: 3.5
output_quality: 90
prompt_strength: 0.7
extra_lora_scale: 1
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "Vibrant Calavera, a portrait photo of VLTA with purple hair wearing a colorful and intricate sugar skull makeup with intricate patterns and designs on her face",
  "extra_lora": "https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 90,
  "prompt_strength": 0.7,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

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

const output = await replicate.run(
  "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
  {
    input: {
      model: "dev",
      prompt: "Vibrant Calavera, a portrait photo of VLTA with purple hair wearing a colorful and intricate sugar skull makeup with intricate patterns and designs on her face",
      extra_lora: "https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor",
      lora_scale: 1,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 90,
      prompt_strength: 0.7,
      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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    input={
        "model": "dev",
        "prompt": "Vibrant Calavera, a portrait photo of VLTA with purple hair wearing a colorful and intricate sugar skull makeup with intricate patterns and designs on her face",
        "extra_lora": "https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor",
        "lora_scale": 1,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 90,
        "prompt_strength": 0.7,
        "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 lucataco/flux-vlta 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": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    "input": {
      "model": "dev",
      "prompt": "Vibrant Calavera, a portrait photo of VLTA with purple hair wearing a colorful and intricate sugar skull makeup with intricate patterns and designs on her face",
      "extra_lora": "https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor",
      "lora_scale": 1,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 90,
      "prompt_strength": 0.7,
      "extra_lora_scale": 1,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-10-09T14:54:00.457444Z",
  "created_at": "2024-10-09T14:53:44.784000Z",
  "data_removed": false,
  "error": null,
  "id": "4cg64vcbt1rm20cje72v097b48",
  "input": {
    "model": "dev",
    "prompt": "Vibrant Calavera, a portrait photo of VLTA with purple hair wearing a colorful and intricate sugar skull makeup with intricate patterns and designs on her face",
    "extra_lora": "https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor",
    "lora_scale": 1,
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 90,
    "prompt_strength": 0.7,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 8269\nPrompt: Vibrant Calavera, a portrait photo of VLTA with purple hair wearing a colorful and intricate sugar skull makeup with intricate patterns and designs on her face\n[!] txt2img mode\nUsing dev model\nLoading extra LoRA weights from: https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor\nfree=6798827577344\nDownloading weights\n2024-10-09T14:53:44Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpwiuzk8cp/weights url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar\n2024-10-09T14:53:46Z | INFO  | [ Complete ] dest=/tmp/tmpwiuzk8cp/weights size=\"172 MB\" total_elapsed=1.158s url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar\nDownloaded weights in 1.19s\nfree=6798653812736\nDownloading weights\n2024-10-09T14:53:46Z | INFO  | [ Initiating ] chunk_size=150M dest=/src/weights-cache/02d0c57a5abd56f3 url=https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor\n2024-10-09T14:53:46Z | INFO  | [ Redirect ] redirect_url=https://civitai-delivery-worker-prod.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/modelVersion/921391/Vibrant_Calavera.safetensors?X-Amz-Expires=86400&response-content-disposition=attachment%3B%20filename%3D%22Vibrant_Calavera.safetensors%22&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=e01358d793ad6966166af8b3064953ad/20241009/us-east-1/s3/aws4_request&X-Amz-Date=20241009T145346Z&X-Amz-SignedHeaders=host&X-Amz-Signature=a6b2431c809fd36a1044bb93fdff62d3335c719fdf83256a76d61a9e8beb1ae5 url=https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor\n2024-10-09T14:53:47Z | INFO  | [ Complete ] dest=/src/weights-cache/02d0c57a5abd56f3 size=\"19 MB\" total_elapsed=0.581s url=https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor\nDownloaded weights in 0.60s\nLoaded LoRAs in 3.29s\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:11,  2.26it/s]\n  7%|▋         | 2/28 [00:00<00:10,  2.48it/s]\n 11%|█         | 3/28 [00:01<00:10,  2.41it/s]\n 14%|█▍        | 4/28 [00:01<00:10,  2.37it/s]\n 18%|█▊        | 5/28 [00:02<00:09,  2.35it/s]\n 21%|██▏       | 6/28 [00:02<00:09,  2.34it/s]\n 25%|██▌       | 7/28 [00:02<00:08,  2.34it/s]\n 29%|██▊       | 8/28 [00:03<00:08,  2.33it/s]\n 32%|███▏      | 9/28 [00:03<00:08,  2.33it/s]\n 36%|███▌      | 10/28 [00:04<00:07,  2.33it/s]\n 39%|███▉      | 11/28 [00:04<00:07,  2.33it/s]\n 43%|████▎     | 12/28 [00:05<00:06,  2.33it/s]\n 46%|████▋     | 13/28 [00:05<00:06,  2.32it/s]\n 50%|█████     | 14/28 [00:05<00:06,  2.32it/s]\n 54%|█████▎    | 15/28 [00:06<00:05,  2.32it/s]\n 57%|█████▋    | 16/28 [00:06<00:05,  2.32it/s]\n 61%|██████    | 17/28 [00:07<00:04,  2.32it/s]\n 64%|██████▍   | 18/28 [00:07<00:04,  2.32it/s]\n 68%|██████▊   | 19/28 [00:08<00:03,  2.32it/s]\n 71%|███████▏  | 20/28 [00:08<00:03,  2.32it/s]\n 75%|███████▌  | 21/28 [00:08<00:03,  2.32it/s]\n 79%|███████▊  | 22/28 [00:09<00:02,  2.32it/s]\n 82%|████████▏ | 23/28 [00:09<00:02,  2.32it/s]\n 86%|████████▌ | 24/28 [00:10<00:01,  2.33it/s]\n 89%|████████▉ | 25/28 [00:10<00:01,  2.33it/s]\n 93%|█████████▎| 26/28 [00:11<00:00,  2.33it/s]\n 96%|█████████▋| 27/28 [00:11<00:00,  2.33it/s]\n100%|██████████| 28/28 [00:12<00:00,  2.32it/s]\n100%|██████████| 28/28 [00:12<00:00,  2.33it/s]",
  "metrics": {
    "predict_time": 15.665560475,
    "total_time": 15.673444
  },
  "output": [
    "https://replicate.delivery/yhqm/sVVamxwaDh7TE5TENpfmLihWTiDRYDoGn8FVLPIc35bEWiyJA/out-0.webp"
  ],
  "started_at": "2024-10-09T14:53:44.791883Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/4cg64vcbt1rm20cje72v097b48",
    "cancel": "https://api.replicate.com/v1/predictions/4cg64vcbt1rm20cje72v097b48/cancel"
  },
  "version": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a"
}

Generated in

15.7 seconds

lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a

Using seed: 8269
Prompt: Vibrant Calavera, a portrait photo of VLTA with purple hair wearing a colorful and intricate sugar skull makeup with intricate patterns and designs on her face
[!] txt2img mode
Using dev model
Loading extra LoRA weights from: https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor
free=6798827577344
Downloading weights
2024-10-09T14:53:44Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmpwiuzk8cp/weights url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar
2024-10-09T14:53:46Z | INFO  | [ Complete ] dest=/tmp/tmpwiuzk8cp/weights size="172 MB" total_elapsed=1.158s url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar
Downloaded weights in 1.19s
free=6798653812736
Downloading weights
2024-10-09T14:53:46Z | INFO  | [ Initiating ] chunk_size=150M dest=/src/weights-cache/02d0c57a5abd56f3 url=https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor
2024-10-09T14:53:46Z | INFO  | [ Redirect ] redirect_url=https://civitai-delivery-worker-prod.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/modelVersion/921391/Vibrant_Calavera.safetensors?X-Amz-Expires=86400&response-content-disposition=attachment%3B%20filename%3D%22Vibrant_Calavera.safetensors%22&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=e01358d793ad6966166af8b3064953ad/20241009/us-east-1/s3/aws4_request&X-Amz-Date=20241009T145346Z&X-Amz-SignedHeaders=host&X-Amz-Signature=a6b2431c809fd36a1044bb93fdff62d3335c719fdf83256a76d61a9e8beb1ae5 url=https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor
2024-10-09T14:53:47Z | INFO  | [ Complete ] dest=/src/weights-cache/02d0c57a5abd56f3 size="19 MB" total_elapsed=0.581s url=https://civitai.com/api/download/models/921391?type=Model&format=SafeTensor
Downloaded weights in 0.60s
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Prediction

Model

6naq7mw1mhrm20cjeb8s9b72e8

Status

Succeeded

Source

Web

Hardware

H100

Total duration

12.7s

Created

7 months ago

Input

model: dev
prompt: portrait photo of VLTA with purple hair
lora_scale: 1
num_outputs: 1
aspect_ratio: 1:1
output_format: webp
guidance_scale: 3.5
output_quality: 90
prompt_strength: 0.8
extra_lora_scale: 1
num_inference_steps: 28

{
  "model": "dev",
  "prompt": "portrait photo of VLTA with purple hair",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 90,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

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

const output = await replicate.run(
  "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
  {
    input: {
      model: "dev",
      prompt: "portrait photo of VLTA with purple hair",
      lora_scale: 1,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 90,
      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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/flux-vlta:e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    input={
        "model": "dev",
        "prompt": "portrait photo of VLTA with purple hair",
        "lora_scale": 1,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 90,
        "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 lucataco/flux-vlta 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": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a",
    "input": {
      "model": "dev",
      "prompt": "portrait photo of VLTA with purple hair",
      "lora_scale": 1,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 90,
      "prompt_strength": 0.8,
      "extra_lora_scale": 1,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-10-09T19:46:38.512107Z",
  "created_at": "2024-10-09T19:46:25.828000Z",
  "data_removed": false,
  "error": null,
  "id": "6naq7mw1mhrm20cjeb8s9b72e8",
  "input": {
    "model": "dev",
    "prompt": "portrait photo of VLTA with purple hair",
    "lora_scale": 1,
    "num_outputs": 1,
    "aspect_ratio": "1:1",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 90,
    "prompt_strength": 0.8,
    "extra_lora_scale": 1,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 30002\nPrompt: portrait photo of VLTA with purple hair\n[!] txt2img mode\nUsing dev model\nfree=6941966012416\nDownloading weights\n2024-10-09T19:46:25Z | INFO  | [ Initiating ] chunk_size=150M dest=/tmp/tmptj37z586/weights url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar\n2024-10-09T19:46:27Z | INFO  | [ Complete ] dest=/tmp/tmptj37z586/weights size=\"172 MB\" total_elapsed=1.853s url=https://replicate.delivery/yhqm/M6dMdD4uIHqPGBBlpbdAJp1uge9x1DHe8v63nzEYfiNA4azmA/trained_model.tar\nDownloaded weights in 1.88s\nLoaded LoRAs in 2.46s\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:09,  2.87it/s]\n  7%|▋         | 2/28 [00:00<00:08,  3.21it/s]\n 11%|█         | 3/28 [00:00<00:08,  3.05it/s]\n 14%|█▍        | 4/28 [00:01<00:08,  2.98it/s]\n 18%|█▊        | 5/28 [00:01<00:07,  2.94it/s]\n 21%|██▏       | 6/28 [00:02<00:07,  2.92it/s]\n 25%|██▌       | 7/28 [00:02<00:07,  2.90it/s]\n 29%|██▊       | 8/28 [00:02<00:06,  2.90it/s]\n 32%|███▏      | 9/28 [00:03<00:06,  2.89it/s]\n 36%|███▌      | 10/28 [00:03<00:06,  2.88it/s]\n 39%|███▉      | 11/28 [00:03<00:05,  2.88it/s]\n 43%|████▎     | 12/28 [00:04<00:05,  2.88it/s]\n 46%|████▋     | 13/28 [00:04<00:05,  2.88it/s]\n 50%|█████     | 14/28 [00:04<00:04,  2.88it/s]\n 54%|█████▎    | 15/28 [00:05<00:04,  2.88it/s]\n 57%|█████▋    | 16/28 [00:05<00:04,  2.88it/s]\n 61%|██████    | 17/28 [00:05<00:03,  2.88it/s]\n 64%|██████▍   | 18/28 [00:06<00:03,  2.88it/s]\n 68%|██████▊   | 19/28 [00:06<00:03,  2.88it/s]\n 71%|███████▏  | 20/28 [00:06<00:02,  2.88it/s]\n 75%|███████▌  | 21/28 [00:07<00:02,  2.88it/s]\n 79%|███████▊  | 22/28 [00:07<00:02,  2.88it/s]\n 82%|████████▏ | 23/28 [00:07<00:01,  2.88it/s]\n 86%|████████▌ | 24/28 [00:08<00:01,  2.88it/s]\n 89%|████████▉ | 25/28 [00:08<00:01,  2.88it/s]\n 93%|█████████▎| 26/28 [00:08<00:00,  2.88it/s]\n 96%|█████████▋| 27/28 [00:09<00:00,  2.88it/s]\n100%|██████████| 28/28 [00:09<00:00,  2.88it/s]\n100%|██████████| 28/28 [00:09<00:00,  2.89it/s]",
  "metrics": {
    "predict_time": 12.682982625,
    "total_time": 12.684107
  },
  "output": [
    "https://replicate.delivery/yhqm/6Hvx5t8qs27gOh5G7jcuLdbmdJ3UA1D9efpL4jLyJcGe8RKnA/out-0.webp"
  ],
  "started_at": "2024-10-09T19:46:25.829124Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/6naq7mw1mhrm20cjeb8s9b72e8",
    "cancel": "https://api.replicate.com/v1/predictions/6naq7mw1mhrm20cjeb8s9b72e8/cancel"
  },
  "version": "e0aeb648e5d574ad729269b07dfb80765f5b169b19aecc9b416a5ce14b43b29a"
}

Generated in

12.7 seconds