aramintak / pop-art-anime

{
  "width": 1024,
  "height": 1024,
  "prompt": "a mouse knight, daiton style",
  "lora_strength": 1,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run aramintak/pop-art-anime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a mouse knight, daiton style",
      lora_strength: 1,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "",
      number_of_images: 1
    }
  }
);

// 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

Import the client:

import replicate

Run aramintak/pop-art-anime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a mouse knight, daiton style",
        "lora_strength": 1,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "",
        "number_of_images": 1
    }
)
print(output)

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

Run aramintak/pop-art-anime 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": "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a mouse knight, daiton style",
      "lora_strength": 1,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-06-07T22:50:43.064036Z",
  "created_at": "2024-06-07T22:50:37.448000Z",
  "data_removed": false,
  "error": null,
  "id": "azg13b4m11rgp0cfykjsedcya8",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "a mouse knight, daiton style",
    "lora_strength": 1,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 3250873027\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 3, title: KSampler, class type: KSampler\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:03,  5.33it/s]\n 10%|█         | 2/20 [00:00<00:03,  5.25it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  5.22it/s]\n 20%|██        | 4/20 [00:00<00:03,  5.21it/s]\n 25%|██▌       | 5/20 [00:00<00:02,  5.21it/s]\n 30%|███       | 6/20 [00:01<00:02,  5.19it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  5.18it/s]\n 40%|████      | 8/20 [00:01<00:02,  5.17it/s]\n 45%|████▌     | 9/20 [00:01<00:02,  5.16it/s]\n 50%|█████     | 10/20 [00:01<00:01,  5.17it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.19it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.18it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.20it/s]\n 70%|███████   | 14/20 [00:02<00:01,  5.22it/s]\n 75%|███████▌  | 15/20 [00:02<00:00,  5.24it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.24it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.25it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.25it/s]\n 95%|█████████▌| 19/20 [00:03<00:00,  5.28it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.31it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.23it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 4.21 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 5.570685,
    "total_time": 5.616036
  },
  "output": [
    "https://replicate.delivery/pbxt/auHmFCZneaQLE6n87oGyOkeeqn8s8Lj1cSZItXKCuO0EGo4lA/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T22:50:37.493351Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/azg13b4m11rgp0cfykjsedcya8",
    "cancel": "https://api.replicate.com/v1/predictions/azg13b4m11rgp0cfykjsedcya8/cancel"
  },
  "version": "a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70"
}

Generated in

5.6 seconds

Tweak it ShareReport

Prediction

aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70

Model

aramintak/pop-art-anime:a59ccb31

z4m5vjermdrgg0cfykjsptcr28

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

5.7s

Created

12 months ago

Input

width: 1024
height: 1024
prompt: a princess with a dress mad of flowers, daiton style
lora_strength: 1
output_format: webp
output_quality: 80
negative_prompt
number_of_images: 1

{
  "width": 1024,
  "height": 1024,
  "prompt": "a princess with a dress mad of flowers, daiton style",
  "lora_strength": 1,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run aramintak/pop-art-anime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a princess with a dress mad of flowers, daiton style",
      lora_strength: 1,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "",
      number_of_images: 1
    }
  }
);

// 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

Import the client:

import replicate

Run aramintak/pop-art-anime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a princess with a dress mad of flowers, daiton style",
        "lora_strength": 1,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "",
        "number_of_images": 1
    }
)
print(output)

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

Run aramintak/pop-art-anime 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": "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a princess with a dress mad of flowers, daiton style",
      "lora_strength": 1,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-06-07T22:51:00.690167Z",
  "created_at": "2024-06-07T22:50:55.011000Z",
  "data_removed": false,
  "error": null,
  "id": "z4m5vjermdrgg0cfykjsptcr28",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "a princess with a dress mad of flowers, daiton style",
    "lora_strength": 1,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 3435930362\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 3, title: KSampler, class type: KSampler\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:03,  5.33it/s]\n 10%|█         | 2/20 [00:00<00:03,  5.23it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  5.23it/s]\n 20%|██        | 4/20 [00:00<00:03,  5.23it/s]\n 25%|██▌       | 5/20 [00:00<00:02,  5.23it/s]\n 30%|███       | 6/20 [00:01<00:02,  5.22it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  5.21it/s]\n 40%|████      | 8/20 [00:01<00:02,  5.21it/s]\n 45%|████▌     | 9/20 [00:01<00:02,  5.20it/s]\n 50%|█████     | 10/20 [00:01<00:01,  5.21it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.23it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.24it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.25it/s]\n 70%|███████   | 14/20 [00:02<00:01,  5.26it/s]\n 75%|███████▌  | 15/20 [00:02<00:00,  5.26it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.26it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.26it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.26it/s]\n 95%|█████████▌| 19/20 [00:03<00:00,  5.30it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.33it/s]\n100%|██████████| 20/20 [00:03<00:00,  5.25it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 4.19 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 5.634936,
    "total_time": 5.679167
  },
  "output": [
    "https://replicate.delivery/pbxt/AKww7pfhPvzqZqeeHPvOqdJGTFvW3KhtAUjBdwA65yeMNQxLB/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T22:50:55.055231Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/z4m5vjermdrgg0cfykjsptcr28",
    "cancel": "https://api.replicate.com/v1/predictions/z4m5vjermdrgg0cfykjsptcr28/cancel"
  },
  "version": "a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70"
}

Generated in

5.6 seconds

Tweak it ShareReport

Prediction

aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70

Model

aramintak/pop-art-anime:a59ccb31

amnrha4am1rgm0cfykp8hqkvbc

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1m 52s

Created

12 months ago

Input

width: 1024
height: 1024
prompt: a happy girl, daiton style
lora_strength: 1
output_format: webp
output_quality: 80
negative_prompt
number_of_images: 1

{
  "width": 1024,
  "height": 1024,
  "prompt": "a happy girl, daiton style",
  "lora_strength": 1,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run aramintak/pop-art-anime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a happy girl, daiton style",
      lora_strength: 1,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "",
      number_of_images: 1
    }
  }
);

// 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

Import the client:

import replicate

Run aramintak/pop-art-anime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a happy girl, daiton style",
        "lora_strength": 1,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "",
        "number_of_images": 1
    }
)
print(output)

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

Run aramintak/pop-art-anime 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": "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a happy girl, daiton style",
      "lora_strength": 1,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-06-07T23:00:05.815784Z",
  "created_at": "2024-06-07T22:58:13.792000Z",
  "data_removed": false,
  "error": null,
  "id": "amnrha4am1rgm0cfykp8hqkvbc",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "a happy girl, daiton style",
    "lora_strength": 1,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 3636985323\nRunning workflow\ngot prompt\nExecuting node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple\nmodel_type EPS\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nclip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']\nloaded straight to GPU\nRequested to load SDXL\nLoading 1 new model\nExecuting node 10, title: Load LoRA, class type: LoraLoader\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 5, title: Empty Latent Image, class type: EmptyLatentImage\nExecuting node 3, title: KSampler, class type: KSampler\nRequested to load SDXL\nLoading 1 new model\n  0%|          | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=14.614643096923828 and t1=14.614643.\nwarnings.warn(f\"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.\")\n  5%|▌         | 1/20 [00:00<00:09,  2.08it/s]\n 10%|█         | 2/20 [00:00<00:05,  3.19it/s]\n 15%|█▌        | 3/20 [00:00<00:04,  3.88it/s]\n 20%|██        | 4/20 [00:01<00:03,  4.31it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  4.60it/s]\n 30%|███       | 6/20 [00:01<00:02,  4.79it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  4.92it/s]\n 40%|████      | 8/20 [00:01<00:02,  5.01it/s]\n 45%|████▌     | 9/20 [00:02<00:02,  5.07it/s]\n 50%|█████     | 10/20 [00:02<00:01,  5.11it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.14it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.16it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.18it/s]\n 70%|███████   | 14/20 [00:02<00:01,  5.19it/s]\n 75%|███████▌  | 15/20 [00:03<00:00,  5.19it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.19it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.19it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.20it/s]\n 95%|█████████▌| 19/20 [00:03<00:00,  5.23it/s]\n100%|██████████| 20/20 [00:04<00:00,  5.26it/s]\n100%|██████████| 20/20 [00:04<00:00,  4.85it/s]\nRequested to load AutoencoderKL\nLoading 1 new model\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 8.51 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 10.424486,
    "total_time": 112.023784
  },
  "output": [
    "https://replicate.delivery/pbxt/As7LqiWvDWJHAtLdc8qnFha7Ykqf5CbrqavFMHil7S36FKeSA/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T22:59:55.391298Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/amnrha4am1rgm0cfykp8hqkvbc",
    "cancel": "https://api.replicate.com/v1/predictions/amnrha4am1rgm0cfykp8hqkvbc/cancel"
  },
  "version": "a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70"
}

Generated in

10.4 seconds

Tweak it ShareReport

Random seed set to: 3636985323
Running workflow
got prompt
Executing node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple
model_type EPS
Using pytorch attention in VAE
Using pytorch attention in VAE
clip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']
loaded straight to GPU
Requested to load SDXL
Loading 1 new model
Executing node 10, title: Load LoRA, class type: LoraLoader
Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Requested to load SDXLClipModel
Loading 1 new model
Executing node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Executing node 5, title: Empty Latent Image, class type: EmptyLatentImage
Executing node 3, title: KSampler, class type: KSampler
Requested to load SDXL
Loading 1 new model
  0%|          | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=14.614643096923828 and t1=14.614643.
warnings.warn(f"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.")
  5%|▌         | 1/20 [00:00<00:09,  2.08it/s]
 10%|█         | 2/20 [00:00<00:05,  3.19it/s]
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Requested to load AutoencoderKL
Loading 1 new model
Executing node 8, title: VAE Decode, class type: VAEDecode
Executing node 9, title: Save Image, class type: SaveImage
Prompt executed in 8.51 seconds
outputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}
====================================
R8__00001_.png

Prediction

aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70

Model

aramintak/pop-art-anime:a59ccb31

cgk6nwcdfhrgm0cfym18keaw68

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1m 40s

Created

12 months ago

Input

width: 1024
height: 1024
prompt: a couple go on a date at an evening cafe, daiton style
lora_strength: 1
output_format: webp
output_quality: 80
negative_prompt
number_of_images: 1

{
  "width": 1024,
  "height": 1024,
  "prompt": "a couple go on a date at an evening cafe, daiton style",
  "lora_strength": 1,
  "output_format": "webp",
  "output_quality": 80,
  "negative_prompt": "",
  "number_of_images": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run aramintak/pop-art-anime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "a couple go on a date at an evening cafe, daiton style",
      lora_strength: 1,
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "",
      number_of_images: 1
    }
  }
);

// 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

Import the client:

import replicate

Run aramintak/pop-art-anime using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "a couple go on a date at an evening cafe, daiton style",
        "lora_strength": 1,
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "",
        "number_of_images": 1
    }
)
print(output)

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

Run aramintak/pop-art-anime 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": "aramintak/pop-art-anime:a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "a couple go on a date at an evening cafe, daiton style",
      "lora_strength": 1,
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-06-07T23:23:56.557990Z",
  "created_at": "2024-06-07T23:22:16.316000Z",
  "data_removed": false,
  "error": null,
  "id": "cgk6nwcdfhrgm0cfym18keaw68",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "a couple go on a date at an evening cafe, daiton style",
    "lora_strength": 1,
    "output_format": "webp",
    "output_quality": 80,
    "negative_prompt": "",
    "number_of_images": 1
  },
  "logs": "Random seed set to: 554574446\nRunning workflow\ngot prompt\nExecuting node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple\nmodel_type EPS\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nclip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']\nloaded straight to GPU\nRequested to load SDXL\nLoading 1 new model\nExecuting node 10, title: Load LoRA, class type: LoraLoader\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 5, title: Empty Latent Image, class type: EmptyLatentImage\nExecuting node 3, title: KSampler, class type: KSampler\nRequested to load SDXL\nLoading 1 new model\n  0%|          | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=14.614643096923828 and t1=14.614643.\nwarnings.warn(f\"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.\")\n  5%|▌         | 1/20 [00:00<00:11,  1.66it/s]\n 10%|█         | 2/20 [00:00<00:06,  2.73it/s]\n 15%|█▌        | 3/20 [00:00<00:04,  3.48it/s]\n 20%|██        | 4/20 [00:01<00:03,  4.01it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  4.37it/s]\n 30%|███       | 6/20 [00:01<00:03,  4.62it/s]\n 35%|███▌      | 7/20 [00:01<00:02,  4.80it/s]\n 40%|████      | 8/20 [00:01<00:02,  4.91it/s]\n 45%|████▌     | 9/20 [00:02<00:02,  5.00it/s]\n 50%|█████     | 10/20 [00:02<00:01,  5.06it/s]\n 55%|█████▌    | 11/20 [00:02<00:01,  5.09it/s]\n 60%|██████    | 12/20 [00:02<00:01,  5.13it/s]\n 65%|██████▌   | 13/20 [00:02<00:01,  5.16it/s]\n 70%|███████   | 14/20 [00:03<00:01,  5.16it/s]\n 75%|███████▌  | 15/20 [00:03<00:00,  5.18it/s]\n 80%|████████  | 16/20 [00:03<00:00,  5.19it/s]\n 85%|████████▌ | 17/20 [00:03<00:00,  5.20it/s]\n 90%|█████████ | 18/20 [00:03<00:00,  5.21it/s]\n 95%|█████████▌| 19/20 [00:04<00:00,  5.23it/s]\n100%|██████████| 20/20 [00:04<00:00,  5.26it/s]\n100%|██████████| 20/20 [00:04<00:00,  4.70it/s]\nRequested to load AutoencoderKL\nLoading 1 new model\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 9.01 seconds\noutputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nR8__00001_.png",
  "metrics": {
    "predict_time": 11.155411,
    "total_time": 100.24199
  },
  "output": [
    "https://replicate.delivery/pbxt/DlgLZsRfL5wzPiuOGlVdvp25G5PCUsGQxVKuCbOWvYlFRKeSA/R8__00001_.webp"
  ],
  "started_at": "2024-06-07T23:23:45.402579Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/cgk6nwcdfhrgm0cfym18keaw68",
    "cancel": "https://api.replicate.com/v1/predictions/cgk6nwcdfhrgm0cfym18keaw68/cancel"
  },
  "version": "a59ccb3185d54e16d3a6ce1452aa0b63ca08e9ee6c81fa4ea8b03201b3aa9b70"
}

Generated in

11.2 seconds

Tweak it ShareReport

Random seed set to: 554574446
Running workflow
got prompt
Executing node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple
model_type EPS
Using pytorch attention in VAE
Using pytorch attention in VAE
clip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']
loaded straight to GPU
Requested to load SDXL
Loading 1 new model
Executing node 10, title: Load LoRA, class type: LoraLoader
Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Requested to load SDXLClipModel
Loading 1 new model
Executing node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode
Executing node 5, title: Empty Latent Image, class type: EmptyLatentImage
Executing node 3, title: KSampler, class type: KSampler
Requested to load SDXL
Loading 1 new model
  0%|          | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=14.614643096923828 and t1=14.614643.
warnings.warn(f"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.")
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Requested to load AutoencoderKL
Loading 1 new model
Executing node 8, title: VAE Decode, class type: VAEDecode
Executing node 9, title: Save Image, class type: SaveImage
Prompt executed in 9.01 seconds
outputs:  {'9': {'images': [{'filename': 'R8__00001_.png', 'subfolder': '', 'type': 'output'}]}}
====================================
R8__00001_.png

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