lucataco / demofusion-enhance

Image to Image enhancer using DemoFusion

Cold

Public
10.6K runs
A100 (80GB)
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Prediction

lucataco/demofusion-enhance:5bcfe110

Model

lucataco/demofusion-enhance:5bcfe110

yyxfu7lb62k5itmg6acv7dpjae

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

3m 15s

Created

over 1 year ago by @fofr

Input

image
scale: 2
sigma: 0.8
prompt: A high resolution photo of a man standing on a hill, fabulous view, clouds
stride: 64
auto_prompt
multi_decoder
cosine_scale_1: 3
cosine_scale_2: 1
cosine_scale_3: 1
guidance_scale: 8.5
negative_prompt: blurry, ugly, duplicate, poorly drawn, deformed, mosaic
view_batch_size: 16
num_inference_steps: 40

{
  "image": "https://replicate.delivery/pbxt/K1EoJ0buGnkhzXnA2egJJpk9mpBaK8UUNbAanwhn3kpUgrm3/out-2-19.png",
  "scale": 2,
  "sigma": 0.8,
  "prompt": "A high resolution photo of a man standing on a hill, fabulous view, clouds",
  "stride": 64,
  "auto_prompt": true,
  "multi_decoder": false,
  "cosine_scale_1": 3,
  "cosine_scale_2": 1,
  "cosine_scale_3": 1,
  "guidance_scale": 8.5,
  "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
  "view_batch_size": 16,
  "num_inference_steps": 40
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
  {
    input: {
      image: "https://replicate.delivery/pbxt/K1EoJ0buGnkhzXnA2egJJpk9mpBaK8UUNbAanwhn3kpUgrm3/out-2-19.png",
      scale: 2,
      sigma: 0.8,
      prompt: "A high resolution photo of a man standing on a hill, fabulous view, clouds",
      stride: 64,
      auto_prompt: true,
      multi_decoder: false,
      cosine_scale_1: 3,
      cosine_scale_2: 1,
      cosine_scale_3: 1,
      guidance_scale: 8.5,
      negative_prompt: "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      view_batch_size: 16,
      num_inference_steps: 40
    }
  }
);
console.log(output);

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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    input={
        "image": "https://replicate.delivery/pbxt/K1EoJ0buGnkhzXnA2egJJpk9mpBaK8UUNbAanwhn3kpUgrm3/out-2-19.png",
        "scale": 2,
        "sigma": 0.8,
        "prompt": "A high resolution photo of a man standing on a hill, fabulous view, clouds",
        "stride": 64,
        "auto_prompt": True,
        "multi_decoder": False,
        "cosine_scale_1": 3,
        "cosine_scale_2": 1,
        "cosine_scale_3": 1,
        "guidance_scale": 8.5,
        "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
        "view_batch_size": 16,
        "num_inference_steps": 40
    }
)
print(output)

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=<paste-your-token-here>

Find your API token in your account settings.

Run lucataco/demofusion-enhance 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": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    "input": {
      "image": "https://replicate.delivery/pbxt/K1EoJ0buGnkhzXnA2egJJpk9mpBaK8UUNbAanwhn3kpUgrm3/out-2-19.png",
      "scale": 2,
      "sigma": 0.8,
      "prompt": "A high resolution photo of a man standing on a hill, fabulous view, clouds",
      "stride": 64,
      "auto_prompt": true,
      "multi_decoder": false,
      "cosine_scale_1": 3,
      "cosine_scale_2": 1,
      "cosine_scale_3": 1,
      "guidance_scale": 8.5,
      "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      "view_batch_size": 16,
      "num_inference_steps": 40
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-12-09T15:08:54.671000Z",
  "created_at": "2023-12-09T15:05:39.223951Z",
  "data_removed": false,
  "error": null,
  "id": "yyxfu7lb62k5itmg6acv7dpjae",
  "input": {
    "image": "https://replicate.delivery/pbxt/K1EoJ0buGnkhzXnA2egJJpk9mpBaK8UUNbAanwhn3kpUgrm3/out-2-19.png",
    "scale": 2,
    "sigma": 0.8,
    "prompt": "A high resolution photo of a man standing on a hill, fabulous view, clouds",
    "stride": 64,
    "auto_prompt": true,
    "multi_decoder": false,
    "cosine_scale_1": 3,
    "cosine_scale_2": 1,
    "cosine_scale_3": 1,
    "guidance_scale": 8.5,
    "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
    "view_batch_size": 16,
    "num_inference_steps": 40
  },
  "logs": "Using seed: 2945029666\n  0%|          | 0/55 [00:00<?, ?it/s]\n 51%|█████     | 28/55 [00:00<00:00, 276.85it/s]\n100%|██████████| 55/55 [00:00<00:00, 293.93it/s]\nFlavor chain:   0%|          | 0/32 [00:00<?, ?it/s]\nFlavor chain:   3%|▎         | 1/32 [00:01<01:01,  1.97s/it]\nFlavor chain:   6%|▋         | 2/32 [00:03<00:59,  1.99s/it]\nFlavor chain:   9%|▉         | 3/32 [00:05<00:57,  2.00s/it]\nFlavor chain:  12%|█▎        | 4/32 [00:08<00:56,  2.01s/it]\nFlavor chain:  16%|█▌        | 5/32 [00:10<00:54,  2.02s/it]\nFlavor chain:  19%|█▉        | 6/32 [00:12<00:52,  2.03s/it]\nFlavor chain:  22%|██▏       | 7/32 [00:14<00:51,  2.05s/it]\nFlavor chain:  25%|██▌       | 8/32 [00:16<00:49,  2.04s/it]\nFlavor chain:  28%|██▊       | 9/32 [00:18<00:47,  2.05s/it]\nFlavor chain:  31%|███▏      | 10/32 [00:20<00:45,  2.06s/it]\nFlavor chain:  34%|███▍      | 11/32 [00:22<00:43,  2.08s/it]\nFlavor chain:  38%|███▊      | 12/32 [00:24<00:42,  2.10s/it]\nFlavor chain:  41%|████  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| 32/50 [00:00<00:00, 311.17it/s]\n100%|██████████| 50/50 [00:00<00:00, 313.35it/s]\nPrompt:  arafed sweater with a christmas tree and snowflakes on a gray background, cinestill 5 0 0, packshot, color block, diagonal lines, woods, elaborate clothing, fox, full product shot, lindsay adler, webbing, city, bright:, hunter, patterned, ax, image, flux, pic, cut, creeper, decoration, bay\n### Phase Encoding ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n0%|          | 0/40 [00:00<?, ?it/s]\n### Phase 1 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:00<00:09,  4.14it/s]\n  5%|▌         | 2/40 [00:00<00:08,  4.24it/s]\n  8%|▊         | 3/40 [00:00<00:08,  4.27it/s]\n 10%|█         | 4/40 [00:00<00:08,  4.28it/s]\n 12%|█▎        | 5/40 [00:01<00:08,  4.29it/s]\n 15%|█▌        | 6/40 [00:01<00:07,  4.29it/s]\n 18%|█▊        | 7/40 [00:01<00:07,  4.30it/s]\n 20%|██        | 8/40 [00:01<00:07,  4.29it/s]\n 22%|██▎       | 9/40 [00:02<00:07,  4.30it/s]\n 25%|██▌      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[00:06<00:02,  4.30it/s]\n 78%|███████▊  | 31/40 [00:07<00:02,  4.30it/s]\n 80%|████████  | 32/40 [00:07<00:01,  4.30it/s]\n 82%|████████▎ | 33/40 [00:07<00:01,  4.30it/s]\n 85%|████████▌ | 34/40 [00:07<00:01,  4.30it/s]\n 88%|████████▊ | 35/40 [00:08<00:01,  4.30it/s]\n 90%|█████████ | 36/40 [00:08<00:00,  4.30it/s]\n 92%|█████████▎| 37/40 [00:08<00:00,  4.30it/s]\n 95%|█████████▌| 38/40 [00:08<00:00,  4.30it/s]\n 98%|█████████▊| 39/40 [00:09<00:00,  4.30it/s]\n### Phase 1 Decoding ###\n100%|██████████| 40/40 [00:09<00:00,  4.30it/s]\n100%|██████████| 40/40 [00:09<00:00,  4.19it/s]\n### Phase 2 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:01<00:51,  1.32s/it]\n  5%|▌         | 2/40 [00:02<00:50,  1.32s/it]\n  8%|▊         | 3/40 [00:03<00:48,  1.32s/it]\n 10%|█         | 4/40 [00:05<00:47,  1.32s/it]\n 12%|█▎        | 5/40 [00:06<00:46,  1.32s/it]\n 15%|█▌        | 6/40 [00:07<00:44,  1.32s/it]\n 18%|█▊        | 7/40 [00:09<00:43,  1.32s/it]\n 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[00:36<00:15,  1.32s/it]\n 72%|███████▎  | 29/40 [00:38<00:14,  1.32s/it]\n 75%|███████▌  | 30/40 [00:39<00:13,  1.32s/it]\n 78%|███████▊  | 31/40 [00:40<00:11,  1.32s/it]\n 80%|████████  | 32/40 [00:42<00:10,  1.32s/it]\n 82%|████████▎ | 33/40 [00:43<00:09,  1.32s/it]\n 85%|████████▌ | 34/40 [00:44<00:07,  1.32s/it]\n 88%|████████▊ | 35/40 [00:46<00:06,  1.32s/it]\n 90%|█████████ | 36/40 [00:47<00:05,  1.32s/it]\n 92%|█████████▎| 37/40 [00:48<00:03,  1.32s/it]\n 95%|█████████▌| 38/40 [00:50<00:02,  1.32s/it]\n 98%|█████████▊| 39/40 [00:51<00:01,  1.32s/it]\n### Phase 2 Decoding ###\n100%|██████████| 40/40 [00:52<00:00,  1.32s/it]\n100%|██████████| 40/40 [00:53<00:00,  1.34s/it]",
  "metrics": {
    "predict_time": 117.661477,
    "total_time": 195.447049
  },
  "output": "https://replicate.delivery/pbxt/MG8jw67ZmI7pKxsFd47ThzAlAmfowUTJYuVtlzOcz7UDqRAJA/out-2.png",
  "started_at": "2023-12-09T15:06:57.009523Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/yyxfu7lb62k5itmg6acv7dpjae",
    "cancel": "https://api.replicate.com/v1/predictions/yyxfu7lb62k5itmg6acv7dpjae/cancel"
  },
  "version": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e"
}

Generated in

1 minute 58 seconds

Tweak it Share Report

Using seed: 2945029666
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Prompt:  arafed sweater with a christmas tree and snowflakes on a gray background, cinestill 5 0 0, packshot, color block, diagonal lines, woods, elaborate clothing, fox, full product shot, lindsay adler, webbing, city, bright:, hunter, patterned, ax, image, flux, pic, cut, creeper, decoration, bay
### Phase Encoding ###
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### Phase 1 Decoding ###
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Prediction

lucataco/demofusion-enhance:5bcfe110

Model

lucataco/demofusion-enhance:5bcfe110

futbmp3bunseptqkhsqozyzodu

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

5m 54s

Created

over 1 year ago

Input

image
scale: 2
sigma: 0.8
stride: 64
auto_prompt
multi_decoder
cosine_scale_1: 3
cosine_scale_2: 1
cosine_scale_3: 1
guidance_scale: 8.5
negative_prompt: blurry, ugly, duplicate, poorly drawn, deformed, mosaic
view_batch_size: 16
num_inference_steps: 40

{
  "image": "https://replicate.delivery/pbxt/K10dBMR5HkR2twsOHUImt6hch8oGy4AuSXnaQT70vayk5OVk/red-flower.jpg",
  "scale": 2,
  "sigma": 0.8,
  "stride": 64,
  "auto_prompt": true,
  "multi_decoder": false,
  "cosine_scale_1": 3,
  "cosine_scale_2": 1,
  "cosine_scale_3": 1,
  "guidance_scale": 8.5,
  "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
  "view_batch_size": 16,
  "num_inference_steps": 40
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
  {
    input: {
      image: "https://replicate.delivery/pbxt/K10dBMR5HkR2twsOHUImt6hch8oGy4AuSXnaQT70vayk5OVk/red-flower.jpg",
      scale: 2,
      sigma: 0.8,
      stride: 64,
      auto_prompt: true,
      multi_decoder: false,
      cosine_scale_1: 3,
      cosine_scale_2: 1,
      cosine_scale_3: 1,
      guidance_scale: 8.5,
      negative_prompt: "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      view_batch_size: 16,
      num_inference_steps: 40
    }
  }
);
console.log(output);

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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    input={
        "image": "https://replicate.delivery/pbxt/K10dBMR5HkR2twsOHUImt6hch8oGy4AuSXnaQT70vayk5OVk/red-flower.jpg",
        "scale": 2,
        "sigma": 0.8,
        "stride": 64,
        "auto_prompt": True,
        "multi_decoder": False,
        "cosine_scale_1": 3,
        "cosine_scale_2": 1,
        "cosine_scale_3": 1,
        "guidance_scale": 8.5,
        "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
        "view_batch_size": 16,
        "num_inference_steps": 40
    }
)
print(output)

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=<paste-your-token-here>

Find your API token in your account settings.

Run lucataco/demofusion-enhance 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": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    "input": {
      "image": "https://replicate.delivery/pbxt/K10dBMR5HkR2twsOHUImt6hch8oGy4AuSXnaQT70vayk5OVk/red-flower.jpg",
      "scale": 2,
      "sigma": 0.8,
      "stride": 64,
      "auto_prompt": true,
      "multi_decoder": false,
      "cosine_scale_1": 3,
      "cosine_scale_2": 1,
      "cosine_scale_3": 1,
      "guidance_scale": 8.5,
      "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      "view_batch_size": 16,
      "num_inference_steps": 40
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-12-08T22:35:30.539992Z",
  "created_at": "2023-12-08T22:29:36.961885Z",
  "data_removed": false,
  "error": null,
  "id": "futbmp3bunseptqkhsqozyzodu",
  "input": {
    "image": "https://replicate.delivery/pbxt/K10dBMR5HkR2twsOHUImt6hch8oGy4AuSXnaQT70vayk5OVk/red-flower.jpg",
    "scale": 2,
    "sigma": 0.8,
    "stride": 64,
    "auto_prompt": true,
    "multi_decoder": false,
    "cosine_scale_1": 3,
    "cosine_scale_2": 1,
    "cosine_scale_3": 1,
    "guidance_scale": 8.5,
    "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
    "view_batch_size": 16,
    "num_inference_steps": 40
  },
  "logs": "Using seed: 2613130750\n  0%|          | 0/55 [00:00<?, ?it/s]\n 45%|████▌     | 25/55 [00:00<00:00, 246.66it/s]\n100%|██████████| 55/55 [00:00<00:00, 277.34it/s]\nFlavor chain:   0%|          | 0/32 [00:00<?, ?it/s]\nFlavor chain:   3%|▎         | 1/32 [00:01<00:58,  1.90s/it]\nFlavor chain:   6%|▋         | 2/32 [00:03<00:58,  1.94s/it]\nFlavor chain:   9%|▉         | 3/32 [00:05<00:56,  1.96s/it]\nFlavor chain:  12%|█▎        | 4/32 [00:07<00:55,  1.98s/it]\nFlavor chain:  16%|█▌        | 5/32 [00:09<00:54,  2.04s/it]\nFlavor chain:  19%|█▉        | 6/32 [00:12<00:54,  2.08s/it]\nFlavor chain:  22%|██▏       | 7/32 [00:14<00:53,  2.12s/it]\nFlavor chain:  25%|██▌       | 8/32 [00:16<00:51,  2.16s/it]\nFlavor chain:  28%|██▊       | 9/32 [00:19<00:52,  2.26s/it]\nFlavor chain:  31%|███▏      | 10/32 [00:21<00:51,  2.35s/it]\nFlavor chain:  31%|███▏      | 10/32 [00:24<00:53,  2.42s/it]\n  0%|          | 0/55 [00:00<?, ?it/s]\n 53%|█████▎    | 29/55 [00:00<00:00, 289.02it/s]\n100%|██████████| 55/55 [00:00<00:00, 299.43it/s]\n  0%|          | 0/6 [00:00<?, ?it/s]\n100%|██████████| 6/6 [00:00<00:00, 237.93it/s]\n  0%|          | 0/50 [00:00<?, ?it/s]\n 64%|██████▍   | 32/50 [00:00<00:00, 310.52it/s]\n100%|██████████| 50/50 [00:00<00:00, 313.61it/s]\nPrompt:  there is a red flower that is on a black background, ultra high res, steven jung, chrysanthemum and hyacinth, 🌻🎹🎼, rich and deep colors, poppy, stunning and rich detail, “ ethereal, solid bacgkround, classic beauty\n### Phase Encoding ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n0%|          | 0/40 [00:00<?, ?it/s]\n### Phase 1 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:00<00:09,  4.21it/s]\n  5%|▌         | 2/40 [00:00<00:08,  4.32it/s]\n  8%|▊         | 3/40 [00:00<00:08,  4.36it/s]\n 10%|█         | 4/40 [00:00<00:08,  4.38it/s]\n 12%|█▎        | 5/40 [00:01<00:07,  4.39it/s]\n 15%|█▌        | 6/40 [00:01<00:07,  4.39it/s]\n 18%|█▊        | 7/40 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  "metrics": {
    "predict_time": 91.089895,
    "total_time": 353.578107
  },
  "output": "https://replicate.delivery/pbxt/6Yq3KtwejJ3WPC8vsv7518ujHlFtcOafJl9S4GeJ1ShihpAkA/out-2.png",
  "started_at": "2023-12-08T22:33:59.450097Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/futbmp3bunseptqkhsqozyzodu",
    "cancel": "https://api.replicate.com/v1/predictions/futbmp3bunseptqkhsqozyzodu/cancel"
  },
  "version": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e"
}

Generated in

1 minute 31 seconds

Tweak it Share Report

Using seed: 2613130750
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Prompt:  there is a red flower that is on a black background, ultra high res, steven jung, chrysanthemum and hyacinth, 🌻🎹🎼, rich and deep colors, poppy, stunning and rich detail, “ ethereal, solid bacgkround, classic beauty
### Phase Encoding ###
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### Phase 1 Decoding ###
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Prediction

lucataco/demofusion-enhance:5bcfe110

Model

lucataco/demofusion-enhance:5bcfe110

xuvor4dbpdflrg7g67gz3wjozy

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

1m 33s

Created

over 1 year ago

Input

image
scale: 2
sigma: 0.8
stride: 64
auto_prompt
multi_decoder
cosine_scale_1: 3
cosine_scale_2: 1
cosine_scale_3: 1
guidance_scale: 8.5
negative_prompt: blurry, ugly, duplicate, poorly drawn, deformed, mosaic
view_batch_size: 16
num_inference_steps: 40

{
  "image": "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
  "scale": 2,
  "sigma": 0.8,
  "stride": 64,
  "auto_prompt": true,
  "multi_decoder": false,
  "cosine_scale_1": 3,
  "cosine_scale_2": 1,
  "cosine_scale_3": 1,
  "guidance_scale": 8.5,
  "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
  "view_batch_size": 16,
  "num_inference_steps": 40
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
  {
    input: {
      image: "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
      scale: 2,
      sigma: 0.8,
      stride: 64,
      auto_prompt: true,
      multi_decoder: false,
      cosine_scale_1: 3,
      cosine_scale_2: 1,
      cosine_scale_3: 1,
      guidance_scale: 8.5,
      negative_prompt: "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      view_batch_size: 16,
      num_inference_steps: 40
    }
  }
);
console.log(output);

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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    input={
        "image": "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
        "scale": 2,
        "sigma": 0.8,
        "stride": 64,
        "auto_prompt": True,
        "multi_decoder": False,
        "cosine_scale_1": 3,
        "cosine_scale_2": 1,
        "cosine_scale_3": 1,
        "guidance_scale": 8.5,
        "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
        "view_batch_size": 16,
        "num_inference_steps": 40
    }
)
print(output)

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=<paste-your-token-here>

Find your API token in your account settings.

Run lucataco/demofusion-enhance 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": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    "input": {
      "image": "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
      "scale": 2,
      "sigma": 0.8,
      "stride": 64,
      "auto_prompt": true,
      "multi_decoder": false,
      "cosine_scale_1": 3,
      "cosine_scale_2": 1,
      "cosine_scale_3": 1,
      "guidance_scale": 8.5,
      "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      "view_batch_size": 16,
      "num_inference_steps": 40
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-12-08T22:39:36.605614Z",
  "created_at": "2023-12-08T22:38:03.368552Z",
  "data_removed": false,
  "error": null,
  "id": "xuvor4dbpdflrg7g67gz3wjozy",
  "input": {
    "image": "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
    "scale": 2,
    "sigma": 0.8,
    "stride": 64,
    "auto_prompt": true,
    "multi_decoder": false,
    "cosine_scale_1": 3,
    "cosine_scale_2": 1,
    "cosine_scale_3": 1,
    "guidance_scale": 8.5,
    "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
    "view_batch_size": 16,
    "num_inference_steps": 40
  },
  "logs": "Using seed: 2418900051\n  0%|          | 0/55 [00:00<?, ?it/s]\n 44%|████▎     | 24/55 [00:00<00:00, 234.03it/s]\n 91%|█████████ | 50/55 [00:00<00:00, 245.82it/s]\n100%|██████████| 55/55 [00:00<00:00, 245.46it/s]\nFlavor chain:   0%|          | 0/32 [00:00<?, ?it/s]\nFlavor chain:   3%|▎         | 1/32 [00:01<00:59,  1.93s/it]\nFlavor chain:   6%|▋         | 2/32 [00:03<00:58,  1.94s/it]\nFlavor chain:   9%|▉         | 3/32 [00:05<00:56,  1.96s/it]\nFlavor chain:  12%|█▎        | 4/32 [00:07<00:55,  1.97s/it]\nFlavor chain:  16%|█▌        | 5/32 [00:09<00:53,  1.99s/it]\nFlavor chain:  19%|█▉        | 6/32 [00:11<00:52,  2.01s/it]\nFlavor chain:  22%|██▏       | 7/32 [00:13<00:50,  2.02s/it]\nFlavor chain:  25%|██▌       | 8/32 [00:16<00:48,  2.04s/it]\nFlavor chain:  28%|██▊       | 9/32 [00:18<00:47,  2.06s/it]\nFlavor chain:  31%|███▏      | 10/32 [00:20<00:45,  2.08s/it]\nFlavor chain:  34%|███▍      | 11/32 [00:22<00:44,  2.10s/it]\nFlavor chain:  38%|███▊      | 12/32 [00:24<00:42,  2.13s/it]\nFlavor chain:  38%|███▊      | 12/32 [00:26<00:44,  2.24s/it]\n  0%|          | 0/55 [00:00<?, ?it/s]\n 45%|████▌     | 25/55 [00:00<00:00, 244.96it/s]\n 93%|█████████▎| 51/55 [00:00<00:00, 250.61it/s]\n100%|██████████| 55/55 [00:00<00:00, 250.56it/s]\n  0%|          | 0/6 [00:00<?, ?it/s]\n100%|██████████| 6/6 [00:00<00:00, 241.91it/s]\n  0%|          | 0/50 [00:00<?, ?it/s]\n 64%|██████▍   | 32/50 [00:00<00:00, 315.42it/s]\n100%|██████████| 50/50 [00:00<00:00, 318.89it/s]\nPrompt:  a close up of a person in a uniform holding a sword, syphon filter, wearing shiny black goggles, big boss, slightly pixelated, dark blue skin, early night, looking into the distance, 64x64, lower half of his body is snake, chilled out smirk on face, dark and stars in the background, centered shoulders up view\n### Phase Encoding ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n0%|          | 0/40 [00:00<?, ?it/s]\n### Phase 1 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  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40/40 [00:09<00:00,  4.30it/s]\n### Phase 2 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:01<00:50,  1.28s/it]\n  5%|▌         | 2/40 [00:02<00:48,  1.29s/it]\n  8%|▊         | 3/40 [00:03<00:47,  1.29s/it]\n 10%|█         | 4/40 [00:05<00:46,  1.29s/it]\n 12%|█▎        | 5/40 [00:06<00:45,  1.29s/it]\n 15%|█▌        | 6/40 [00:07<00:43,  1.29s/it]\n 18%|█▊        | 7/40 [00:09<00:42,  1.29s/it]\n 20%|██        | 8/40 [00:10<00:41,  1.29s/it]\n 22%|██▎       | 9/40 [00:11<00:39,  1.29s/it]\n 25%|██▌       | 10/40 [00:12<00:38,  1.29s/it]\n 28%|██▊       | 11/40 [00:14<00:37,  1.29s/it]\n 30%|███       | 12/40 [00:15<00:36,  1.29s/it]\n 32%|███▎      | 13/40 [00:16<00:34,  1.29s/it]\n 35%|███▌      | 14/40 [00:18<00:33,  1.29s/it]\n 38%|███▊      | 15/40 [00:19<00:32,  1.29s/it]\n 40%|████      | 16/40 [00:20<00:30,  1.29s/it]\n 42%|████▎     | 17/40 [00:21<00:29,  1.29s/it]\n 45%|████▌     | 18/40 [00:23<00:28,  1.29s/it]\n 48%|████▊     | 19/40 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1.29s/it]\n### Phase 2 Decoding ###\n100%|██████████| 40/40 [00:51<00:00,  1.29s/it]\n100%|██████████| 40/40 [00:52<00:00,  1.31s/it]",
  "metrics": {
    "predict_time": 93.199234,
    "total_time": 93.237062
  },
  "output": "https://replicate.delivery/pbxt/WjOeXFNnL6V2OyKBns3LWio01hsHKRpwmxy9tSILQ9sTaKAJA/out-2.png",
  "started_at": "2023-12-08T22:38:03.406380Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/xuvor4dbpdflrg7g67gz3wjozy",
    "cancel": "https://api.replicate.com/v1/predictions/xuvor4dbpdflrg7g67gz3wjozy/cancel"
  },
  "version": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e"
}

Generated in

1 minute 33 seconds

Tweak it Share Report

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Prompt:  a close up of a person in a uniform holding a sword, syphon filter, wearing shiny black goggles, big boss, slightly pixelated, dark blue skin, early night, looking into the distance, 64x64, lower half of his body is snake, chilled out smirk on face, dark and stars in the background, centered shoulders up view
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### Phase 1 Decoding ###
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### Phase 2 Decoding ###
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Prediction

lucataco/demofusion-enhance:5bcfe110

Model

lucataco/demofusion-enhance:5bcfe110

uvz2uflbsyozfak6i5n6em4irq

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

1m 33s

Created

over 1 year ago

Input

image
scale: 2
sigma: 0.8
prompt: A high resolution photo
stride: 64
auto_prompt
multi_decoder
cosine_scale_1: 3
cosine_scale_2: 1
cosine_scale_3: 1
guidance_scale: 8.5
negative_prompt: blurry, ugly, duplicate, poorly drawn, deformed, mosaic
view_batch_size: 16
num_inference_steps: 40

{
  "image": "https://replicate.delivery/pbxt/K10oPBW66vKyg5N40mhCEzCGps3rcGrWTInarrtWa0oD9Eq1/lowres-dog.png",
  "scale": 2,
  "sigma": 0.8,
  "prompt": "A high resolution photo",
  "stride": 64,
  "auto_prompt": true,
  "multi_decoder": false,
  "cosine_scale_1": 3,
  "cosine_scale_2": 1,
  "cosine_scale_3": 1,
  "guidance_scale": 8.5,
  "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
  "view_batch_size": 16,
  "num_inference_steps": 40
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
  {
    input: {
      image: "https://replicate.delivery/pbxt/K10oPBW66vKyg5N40mhCEzCGps3rcGrWTInarrtWa0oD9Eq1/lowres-dog.png",
      scale: 2,
      sigma: 0.8,
      prompt: "A high resolution photo",
      stride: 64,
      auto_prompt: true,
      multi_decoder: false,
      cosine_scale_1: 3,
      cosine_scale_2: 1,
      cosine_scale_3: 1,
      guidance_scale: 8.5,
      negative_prompt: "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      view_batch_size: 16,
      num_inference_steps: 40
    }
  }
);
console.log(output);

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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    input={
        "image": "https://replicate.delivery/pbxt/K10oPBW66vKyg5N40mhCEzCGps3rcGrWTInarrtWa0oD9Eq1/lowres-dog.png",
        "scale": 2,
        "sigma": 0.8,
        "prompt": "A high resolution photo",
        "stride": 64,
        "auto_prompt": True,
        "multi_decoder": False,
        "cosine_scale_1": 3,
        "cosine_scale_2": 1,
        "cosine_scale_3": 1,
        "guidance_scale": 8.5,
        "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
        "view_batch_size": 16,
        "num_inference_steps": 40
    }
)
print(output)

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=<paste-your-token-here>

Find your API token in your account settings.

Run lucataco/demofusion-enhance 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": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    "input": {
      "image": "https://replicate.delivery/pbxt/K10oPBW66vKyg5N40mhCEzCGps3rcGrWTInarrtWa0oD9Eq1/lowres-dog.png",
      "scale": 2,
      "sigma": 0.8,
      "prompt": "A high resolution photo",
      "stride": 64,
      "auto_prompt": true,
      "multi_decoder": false,
      "cosine_scale_1": 3,
      "cosine_scale_2": 1,
      "cosine_scale_3": 1,
      "guidance_scale": 8.5,
      "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      "view_batch_size": 16,
      "num_inference_steps": 40
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-12-08T22:43:00.547710Z",
  "created_at": "2023-12-08T22:41:27.466972Z",
  "data_removed": false,
  "error": null,
  "id": "uvz2uflbsyozfak6i5n6em4irq",
  "input": {
    "image": "https://replicate.delivery/pbxt/K10oPBW66vKyg5N40mhCEzCGps3rcGrWTInarrtWa0oD9Eq1/lowres-dog.png",
    "scale": 2,
    "sigma": 0.8,
    "prompt": "A high resolution photo",
    "stride": 64,
    "auto_prompt": true,
    "multi_decoder": false,
    "cosine_scale_1": 3,
    "cosine_scale_2": 1,
    "cosine_scale_3": 1,
    "guidance_scale": 8.5,
    "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
    "view_batch_size": 16,
    "num_inference_steps": 40
  },
  "logs": "Using seed: 3935140720\n  0%|          | 0/55 [00:00<?, ?it/s]\n 38%|███▊      | 21/55 [00:00<00:00, 96.59it/s]\n 84%|████████▎ | 46/55 [00:00<00:00, 156.27it/s]\n100%|██████████| 55/55 [00:00<00:00, 155.29it/s]\nFlavor chain:   0%|          | 0/32 [00:00<?, ?it/s]\nFlavor chain:   3%|▎         | 1/32 [00:01<00:59,  1.93s/it]\nFlavor chain:   6%|▋         | 2/32 [00:03<00:58,  1.95s/it]\nFlavor chain:   9%|▉         | 3/32 [00:05<00:56,  1.96s/it]\nFlavor chain:  12%|█▎        | 4/32 [00:07<00:55,  1.99s/it]\nFlavor chain:  16%|█▌        | 5/32 [00:09<00:54,  2.01s/it]\nFlavor chain:  19%|█▉        | 6/32 [00:12<00:53,  2.07s/it]\nFlavor chain:  22%|██▏       | 7/32 [00:14<00:53,  2.13s/it]\nFlavor chain:  25%|██▌       | 8/32 [00:16<00:52,  2.17s/it]\nFlavor chain:  28%|██▊       | 9/32 [00:18<00:50,  2.20s/it]\nFlavor chain:  31%|███▏      | 10/32 [00:21<00:48,  2.23s/it]\nFlavor chain:  34%|███▍      | 11/32 [00:23<00:47,  2.25s/it]\nFlavor chain:  34%|███▍      | 11/32 [00:25<00:49,  2.35s/it]\n  0%|          | 0/55 [00:00<?, ?it/s]\n 42%|████▏     | 23/55 [00:00<00:00, 229.65it/s]\n 89%|████████▉ | 49/55 [00:00<00:00, 242.37it/s]\n100%|██████████| 55/55 [00:00<00:00, 242.84it/s]\n  0%|          | 0/6 [00:00<?, ?it/s]\n100%|██████████| 6/6 [00:00<00:00, 240.03it/s]\n  0%|          | 0/50 [00:00<?, ?it/s]\n 64%|██████▍   | 32/50 [00:00<00:00, 313.64it/s]\n100%|██████████| 50/50 [00:00<00:00, 316.96it/s]\nPrompt:  araffe dog wearing a party hat and a bow tie, depicting a corgi made of fire, pexels, 256x256, at a birthday party, фото девушка курит, 2012, adopt, :6, corgi, niko oneshot riding a roomba, us\n### Phase Encoding ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n0%|          | 0/40 [00:00<?, ?it/s]\n### Phase 1 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:00<00:08,  4.42it/s]\n  5%|▌         | 2/40 [00:00<00:08,  4.42it/s]\n  8%|▊         | 3/40 [00:00<00:08,  4.41it/s]\n 10%|█         | 4/40 [00:00<00:08,  4.41it/s]\n 12%|█▎        | 5/40 [00:01<00:07,  4.40it/s]\n 15%|█▌        | 6/40 [00:01<00:07,  4.40it/s]\n 18%|█▊        | 7/40 [00:01<00:07,  4.40it/s]\n 20%|██        | 8/40 [00:01<00:07,  4.40it/s]\n 22%|██▎       | 9/40 [00:02<00:07,  4.40it/s]\n 25%|██▌       | 10/40 [00:02<00:06,  4.40it/s]\n 28%|██▊       | 11/40 [00:02<00:06,  4.40it/s]\n 30%|███       | 12/40 [00:02<00:06,  4.40it/s]\n 32%|███▎      | 13/40 [00:02<00:06,  4.40it/s]\n 35%|███▌      | 14/40 [00:03<00:05,  4.40it/s]\n 38%|███▊      | 15/40 [00:03<00:05,  4.40it/s]\n 40%|████      | 16/40 [00:03<00:05,  4.40it/s]\n 42%|████▎     | 17/40 [00:03<00:05,  4.40it/s]\n 45%|████▌     | 18/40 [00:04<00:04,  4.40it/s]\n 48%|████▊     | 19/40 [00:04<00:04,  4.40it/s]\n 50%|█████     | 20/40 [00:04<00:04,  4.40it/s]\n 52%|█████▎    | 21/40 [00:04<00:04,  4.40it/s]\n 55%|█████▌    | 22/40 [00:04<00:04,  4.40it/s]\n 57%|█████▊    | 23/40 [00:05<00:03,  4.40it/s]\n 60%|██████    | 24/40 [00:05<00:03,  4.39it/s]\n 62%|██████▎   | 25/40 [00:05<00:03,  4.39it/s]\n 65%|██████▌   | 26/40 [00:05<00:03,  4.39it/s]\n 68%|██████▊   | 27/40 [00:06<00:02,  4.39it/s]\n 70%|███████   | 28/40 [00:06<00:02,  4.39it/s]\n 72%|███████▎  | 29/40 [00:06<00:02,  4.39it/s]\n 75%|███████▌  | 30/40 [00:06<00:02,  4.39it/s]\n 78%|███████▊  | 31/40 [00:07<00:02,  4.40it/s]\n 80%|████████  | 32/40 [00:07<00:01,  4.40it/s]\n 82%|████████▎ | 33/40 [00:07<00:01,  4.40it/s]\n 85%|████████▌ | 34/40 [00:07<00:01,  4.40it/s]\n 88%|████████▊ | 35/40 [00:07<00:01,  4.40it/s]\n 90%|█████████ | 36/40 [00:08<00:00,  4.40it/s]\n 92%|█████████▎| 37/40 [00:08<00:00,  4.40it/s]\n 95%|█████████▌| 38/40 [00:08<00:00,  4.40it/s]\n 98%|█████████▊| 39/40 [00:08<00:00,  4.40it/s]\n### Phase 1 Decoding ###\n100%|██████████| 40/40 [00:09<00:00,  4.40it/s]\n100%|██████████| 40/40 [00:09<00:00,  4.30it/s]\n### Phase 2 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:01<00:50,  1.29s/it]\n  5%|▌         | 2/40 [00:02<00:48,  1.29s/it]\n  8%|▊         | 3/40 [00:03<00:47,  1.29s/it]\n 10%|█         | 4/40 [00:05<00:46,  1.29s/it]\n 12%|█▎        | 5/40 [00:06<00:45,  1.29s/it]\n 15%|█▌        | 6/40 [00:07<00:43,  1.29s/it]\n 18%|█▊        | 7/40 [00:09<00:42,  1.29s/it]\n 20%|██        | 8/40 [00:10<00:41,  1.29s/it]\n 22%|██▎       | 9/40 [00:11<00:39,  1.29s/it]\n 25%|██▌       | 10/40 [00:12<00:38,  1.29s/it]\n 28%|██▊       | 11/40 [00:14<00:37,  1.29s/it]\n 30%|███       | 12/40 [00:15<00:36,  1.29s/it]\n 32%|███▎      | 13/40 [00:16<00:34,  1.29s/it]\n 35%|███▌      | 14/40 [00:18<00:33,  1.29s/it]\n 38%|███▊      | 15/40 [00:19<00:32,  1.29s/it]\n 40%|████      | 16/40 [00:20<00:30,  1.29s/it]\n 42%|████▎     | 17/40 [00:21<00:29,  1.29s/it]\n 45%|████▌     | 18/40 [00:23<00:28,  1.29s/it]\n 48%|████▊     | 19/40 [00:24<00:27,  1.29s/it]\n 50%|█████     | 20/40 [00:25<00:25,  1.29s/it]\n 52%|█████▎    | 21/40 [00:27<00:24,  1.29s/it]\n 55%|█████▌    | 22/40 [00:28<00:23,  1.29s/it]\n 57%|█████▊    | 23/40 [00:29<00:21,  1.29s/it]\n 60%|██████    | 24/40 [00:30<00:20,  1.29s/it]\n 62%|██████▎   | 25/40 [00:32<00:19,  1.29s/it]\n 65%|██████▌   | 26/40 [00:33<00:18,  1.29s/it]\n 68%|██████▊   | 27/40 [00:34<00:16,  1.29s/it]\n 70%|███████   | 28/40 [00:36<00:15,  1.29s/it]\n 72%|███████▎  | 29/40 [00:37<00:14,  1.29s/it]\n 75%|███████▌  | 30/40 [00:38<00:12,  1.29s/it]\n 78%|███████▊  | 31/40 [00:39<00:11,  1.29s/it]\n 80%|████████  | 32/40 [00:41<00:10,  1.29s/it]\n 82%|████████▎ | 33/40 [00:42<00:09,  1.29s/it]\n 85%|████████▌ | 34/40 [00:43<00:07,  1.29s/it]\n 88%|████████▊ | 35/40 [00:45<00:06,  1.29s/it]\n 90%|█████████ | 36/40 [00:46<00:05,  1.29s/it]\n 92%|█████████▎| 37/40 [00:47<00:03,  1.29s/it]\n 95%|█████████▌| 38/40 [00:49<00:02,  1.29s/it]\n 98%|█████████▊| 39/40 [00:50<00:01,  1.29s/it]\n### Phase 2 Decoding ###\n100%|██████████| 40/40 [00:51<00:00,  1.29s/it]\n100%|██████████| 40/40 [00:52<00:00,  1.31s/it]",
  "metrics": {
    "predict_time": 93.043527,
    "total_time": 93.080738
  },
  "output": "https://replicate.delivery/pbxt/kSFd5oH8lNoRKdDxlpoZeJM6TY7b6ggfExG1WlqF1ACz3UASA/out-2.png",
  "started_at": "2023-12-08T22:41:27.504183Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/uvz2uflbsyozfak6i5n6em4irq",
    "cancel": "https://api.replicate.com/v1/predictions/uvz2uflbsyozfak6i5n6em4irq/cancel"
  },
  "version": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e"
}

Generated in

1 minute 33 seconds

Tweak it Share Report

Using seed: 3935140720
  0%|          | 0/55 [00:00<?, ?it/s]
 38%|███▊      | 21/55 [00:00<00:00, 96.59it/s]
 84%|████████▎ | 46/55 [00:00<00:00, 156.27it/s]
100%|██████████| 55/55 [00:00<00:00, 155.29it/s]
Flavor chain:   0%|          | 0/32 [00:00<?, ?it/s]
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Flavor chain:   9%|▉         | 3/32 [00:05<00:56,  1.96s/it]
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Flavor chain:  34%|███▍      | 11/32 [00:25<00:49,  2.35s/it]
  0%|          | 0/55 [00:00<?, ?it/s]
 42%|████▏     | 23/55 [00:00<00:00, 229.65it/s]
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 64%|██████▍   | 32/50 [00:00<00:00, 313.64it/s]
100%|██████████| 50/50 [00:00<00:00, 316.96it/s]
Prompt:  araffe dog wearing a party hat and a bow tie, depicting a corgi made of fire, pexels, 256x256, at a birthday party, фото девушка курит, 2012, adopt, :6, corgi, niko oneshot riding a roomba, us
### Phase Encoding ###
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0%|          | 0/40 [00:00<?, ?it/s]
### Phase 1 Denoising ###
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### Phase 1 Decoding ###
100%|██████████| 40/40 [00:09<00:00,  4.40it/s]
100%|██████████| 40/40 [00:09<00:00,  4.30it/s]
### Phase 2 Denoising ###
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### Phase 2 Decoding ###
100%|██████████| 40/40 [00:51<00:00,  1.29s/it]
100%|██████████| 40/40 [00:52<00:00,  1.31s/it]

Prediction

lucataco/demofusion-enhance:5bcfe110

Model

lucataco/demofusion-enhance:5bcfe110

v4mpr4tb7s4wyj37qbgc3go3me

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

1m 32s

Created

over 1 year ago

Input

image
scale: 2
sigma: 0.8
stride: 64
auto_prompt
multi_decoder
cosine_scale_1: 3
cosine_scale_2: 1
cosine_scale_3: 1
guidance_scale: 8.5
negative_prompt: blurry, ugly, duplicate, poorly drawn, deformed, mosaic
view_batch_size: 16
num_inference_steps: 40

{
  "image": "https://replicate.delivery/pbxt/K10undbkZmzfW1rV9eG3lYhpNtull1tFogKcDGhaYFhGNAPS/joker.png",
  "scale": 2,
  "sigma": 0.8,
  "stride": 64,
  "auto_prompt": true,
  "multi_decoder": false,
  "cosine_scale_1": 3,
  "cosine_scale_2": 1,
  "cosine_scale_3": 1,
  "guidance_scale": 8.5,
  "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
  "view_batch_size": 16,
  "num_inference_steps": 40
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
  {
    input: {
      image: "https://replicate.delivery/pbxt/K10undbkZmzfW1rV9eG3lYhpNtull1tFogKcDGhaYFhGNAPS/joker.png",
      scale: 2,
      sigma: 0.8,
      stride: 64,
      auto_prompt: true,
      multi_decoder: false,
      cosine_scale_1: 3,
      cosine_scale_2: 1,
      cosine_scale_3: 1,
      guidance_scale: 8.5,
      negative_prompt: "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      view_batch_size: 16,
      num_inference_steps: 40
    }
  }
);
console.log(output);

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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

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

output = replicate.run(
    "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    input={
        "image": "https://replicate.delivery/pbxt/K10undbkZmzfW1rV9eG3lYhpNtull1tFogKcDGhaYFhGNAPS/joker.png",
        "scale": 2,
        "sigma": 0.8,
        "stride": 64,
        "auto_prompt": True,
        "multi_decoder": False,
        "cosine_scale_1": 3,
        "cosine_scale_2": 1,
        "cosine_scale_3": 1,
        "guidance_scale": 8.5,
        "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
        "view_batch_size": 16,
        "num_inference_steps": 40
    }
)
print(output)

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=<paste-your-token-here>

Find your API token in your account settings.

Run lucataco/demofusion-enhance 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": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    "input": {
      "image": "https://replicate.delivery/pbxt/K10undbkZmzfW1rV9eG3lYhpNtull1tFogKcDGhaYFhGNAPS/joker.png",
      "scale": 2,
      "sigma": 0.8,
      "stride": 64,
      "auto_prompt": true,
      "multi_decoder": false,
      "cosine_scale_1": 3,
      "cosine_scale_2": 1,
      "cosine_scale_3": 1,
      "guidance_scale": 8.5,
      "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      "view_batch_size": 16,
      "num_inference_steps": 40
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-12-08T22:49:45.115885Z",
  "created_at": "2023-12-08T22:48:13.040721Z",
  "data_removed": false,
  "error": null,
  "id": "v4mpr4tb7s4wyj37qbgc3go3me",
  "input": {
    "image": "https://replicate.delivery/pbxt/K10undbkZmzfW1rV9eG3lYhpNtull1tFogKcDGhaYFhGNAPS/joker.png",
    "scale": 2,
    "sigma": 0.8,
    "stride": 64,
    "auto_prompt": true,
    "multi_decoder": false,
    "cosine_scale_1": 3,
    "cosine_scale_2": 1,
    "cosine_scale_3": 1,
    "guidance_scale": 8.5,
    "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
    "view_batch_size": 16,
    "num_inference_steps": 40
  },
  "logs": "Using seed: 2189538684\n  0%|          | 0/55 [00:00<?, ?it/s]\n 44%|████▎     | 24/55 [00:00<00:00, 237.08it/s]\n 91%|█████████ | 50/55 [00:00<00:00, 247.09it/s]\n100%|██████████| 55/55 [00:00<00:00, 247.05it/s]\nFlavor chain:   0%|          | 0/32 [00:00<?, ?it/s]\nFlavor chain:   3%|▎         | 1/32 [00:01<00:59,  1.94s/it]\nFlavor chain:   6%|▋         | 2/32 [00:03<00:58,  1.96s/it]\nFlavor chain:   9%|▉         | 3/32 [00:05<00:57,  1.97s/it]\nFlavor chain:  12%|█▎        | 4/32 [00:07<00:55,  1.99s/it]\nFlavor chain:  16%|█▌        | 5/32 [00:09<00:54,  2.01s/it]\nFlavor chain:  19%|█▉        | 6/32 [00:12<00:52,  2.02s/it]\nFlavor chain:  22%|██▏       | 7/32 [00:14<00:51,  2.04s/it]\nFlavor chain:  25%|██▌       | 8/32 [00:16<00:49,  2.06s/it]\nFlavor chain:  28%|██▊       | 9/32 [00:18<00:47,  2.07s/it]\nFlavor chain:  31%|███▏      | 10/32 [00:20<00:45,  2.08s/it]\nFlavor chain:  34%|███▍      | 11/32 [00:22<00:44,  2.10s/it]\nFlavor chain:  34%|███▍      | 11/32 [00:24<00:47,  2.25s/it]\n  0%|          | 0/55 [00:00<?, ?it/s]\n 44%|████▎     | 24/55 [00:00<00:00, 233.50it/s]\n 91%|█████████ | 50/55 [00:00<00:00, 244.80it/s]\n100%|██████████| 55/55 [00:00<00:00, 244.91it/s]\n  0%|          | 0/6 [00:00<?, ?it/s]\n100%|██████████| 6/6 [00:00<00:00, 234.67it/s]\n  0%|          | 0/50 [00:00<?, ?it/s]\n 64%|██████▍   | 32/50 [00:00<00:00, 313.71it/s]\n100%|██████████| 50/50 [00:00<00:00, 317.68it/s]\nPrompt:  joker walking down the street in a red suit and purple gloves, photorealistic octane 3d render, as action figures, full body photoshoot, on the runway, hottoys, 2 0 2 2 photo, high-quality photo, red yellow, with highly detailed, cosplay photo, sci - fi -\n### Phase Encoding ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n0%|          | 0/40 [00:00<?, ?it/s]\n### Phase 1 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:00<00:08,  4.41it/s]\n  5%|▌         | 2/40 [00:00<00:08,  4.41it/s]\n  8%|▊         | 3/40 [00:00<00:08,  4.40it/s]\n 10%|█         | 4/40 [00:00<00:08,  4.40it/s]\n 12%|█▎        | 5/40 [00:01<00:07,  4.40it/s]\n 15%|█▌        | 6/40 [00:01<00:07,  4.40it/s]\n 18%|█▊        | 7/40 [00:01<00:07,  4.40it/s]\n 20%|██        | 8/40 [00:01<00:07,  4.40it/s]\n 22%|██▎       | 9/40 [00:02<00:07,  4.40it/s]\n 25%|██▌       | 10/40 [00:02<00:06,  4.40it/s]\n 28%|██▊       | 11/40 [00:02<00:06,  4.40it/s]\n 30%|███       | 12/40 [00:02<00:06,  4.40it/s]\n 32%|███▎      | 13/40 [00:02<00:06,  4.40it/s]\n 35%|███▌      | 14/40 [00:03<00:05,  4.40it/s]\n 38%|███▊      | 15/40 [00:03<00:05,  4.40it/s]\n 40%|████      | 16/40 [00:03<00:05,  4.40it/s]\n 42%|████▎     | 17/40 [00:03<00:05,  4.40it/s]\n 45%|████▌     | 18/40 [00:04<00:05,  4.40it/s]\n 48%|████▊     | 19/40 [00:04<00:04,  4.40it/s]\n 50%|█████     | 20/40 [00:04<00:04,  4.40it/s]\n 52%|█████▎    | 21/40 [00:04<00:04,  4.40it/s]\n 55%|█████▌    | 22/40 [00:05<00:04,  4.40it/s]\n 57%|█████▊    | 23/40 [00:05<00:03,  4.40it/s]\n 60%|██████    | 24/40 [00:05<00:03,  4.40it/s]\n 62%|██████▎   | 25/40 [00:05<00:03,  4.40it/s]\n 65%|██████▌   | 26/40 [00:05<00:03,  4.40it/s]\n 68%|██████▊   | 27/40 [00:06<00:02,  4.40it/s]\n 70%|███████   | 28/40 [00:06<00:02,  4.40it/s]\n 72%|███████▎  | 29/40 [00:06<00:02,  4.40it/s]\n 75%|███████▌  | 30/40 [00:06<00:02,  4.40it/s]\n 78%|███████▊  | 31/40 [00:07<00:02,  4.40it/s]\n 80%|████████  | 32/40 [00:07<00:01,  4.40it/s]\n 82%|████████▎ | 33/40 [00:07<00:01,  4.40it/s]\n 85%|████████▌ | 34/40 [00:07<00:01,  4.40it/s]\n 88%|████████▊ | 35/40 [00:07<00:01,  4.40it/s]\n 90%|█████████ | 36/40 [00:08<00:00,  4.40it/s]\n 92%|█████████▎| 37/40 [00:08<00:00,  4.40it/s]\n 95%|█████████▌| 38/40 [00:08<00:00,  4.40it/s]\n 98%|█████████▊| 39/40 [00:08<00:00,  4.40it/s]\n### Phase 1 Decoding ###\n100%|██████████| 40/40 [00:09<00:00,  4.40it/s]\n100%|██████████| 40/40 [00:09<00:00,  4.29it/s]\n### Phase 2 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:01<00:50,  1.29s/it]\n  5%|▌         | 2/40 [00:02<00:48,  1.29s/it]\n  8%|▊         | 3/40 [00:03<00:47,  1.29s/it]\n 10%|█         | 4/40 [00:05<00:46,  1.29s/it]\n 12%|█▎        | 5/40 [00:06<00:45,  1.29s/it]\n 15%|█▌        | 6/40 [00:07<00:43,  1.29s/it]\n 18%|█▊        | 7/40 [00:09<00:42,  1.29s/it]\n 20%|██        | 8/40 [00:10<00:41,  1.29s/it]\n 22%|██▎       | 9/40 [00:11<00:39,  1.29s/it]\n 25%|██▌       | 10/40 [00:12<00:38,  1.29s/it]\n 28%|██▊       | 11/40 [00:14<00:37,  1.29s/it]\n 30%|███       | 12/40 [00:15<00:36,  1.29s/it]\n 32%|███▎      | 13/40 [00:16<00:34,  1.29s/it]\n 35%|███▌      | 14/40 [00:18<00:33,  1.29s/it]\n 38%|███▊      | 15/40 [00:19<00:32,  1.29s/it]\n 40%|████      | 16/40 [00:20<00:30,  1.29s/it]\n 42%|████▎     | 17/40 [00:21<00:29,  1.29s/it]\n 45%|████▌     | 18/40 [00:23<00:28,  1.29s/it]\n 48%|████▊     | 19/40 [00:24<00:27,  1.29s/it]\n 50%|█████     | 20/40 [00:25<00:25,  1.29s/it]\n 52%|█████▎    | 21/40 [00:27<00:24,  1.29s/it]\n 55%|█████▌    | 22/40 [00:28<00:23,  1.29s/it]\n 57%|█████▊    | 23/40 [00:29<00:21,  1.29s/it]\n 60%|██████    | 24/40 [00:30<00:20,  1.29s/it]\n 62%|██████▎   | 25/40 [00:32<00:19,  1.29s/it]\n 65%|██████▌   | 26/40 [00:33<00:18,  1.29s/it]\n 68%|██████▊   | 27/40 [00:34<00:16,  1.29s/it]\n 70%|███████   | 28/40 [00:36<00:15,  1.29s/it]\n 72%|███████▎  | 29/40 [00:37<00:14,  1.29s/it]\n 75%|███████▌  | 30/40 [00:38<00:12,  1.29s/it]\n 78%|███████▊  | 31/40 [00:39<00:11,  1.29s/it]\n 80%|████████  | 32/40 [00:41<00:10,  1.29s/it]\n 82%|████████▎ | 33/40 [00:42<00:09,  1.29s/it]\n 85%|████████▌ | 34/40 [00:43<00:07,  1.29s/it]\n 88%|████████▊ | 35/40 [00:45<00:06,  1.29s/it]\n 90%|█████████ | 36/40 [00:46<00:05,  1.29s/it]\n 92%|█████████▎| 37/40 [00:47<00:03,  1.29s/it]\n 95%|█████████▌| 38/40 [00:48<00:02,  1.29s/it]\n 98%|█████████▊| 39/40 [00:50<00:01,  1.29s/it]\n### Phase 2 Decoding ###\n100%|██████████| 40/40 [00:51<00:00,  1.29s/it]\n100%|██████████| 40/40 [00:52<00:00,  1.31s/it]",
  "metrics": {
    "predict_time": 92.039373,
    "total_time": 92.075164
  },
  "output": "https://replicate.delivery/pbxt/fJz1ONExG8xlF6vQ3jqjyZffp74XNpBlz3fhJcdljqti4TBIB/out-2.png",
  "started_at": "2023-12-08T22:48:13.076512Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/v4mpr4tb7s4wyj37qbgc3go3me",
    "cancel": "https://api.replicate.com/v1/predictions/v4mpr4tb7s4wyj37qbgc3go3me/cancel"
  },
  "version": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e"
}

Generated in

1 minute 32 seconds

Tweak it Share Report

Using seed: 2189538684
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Prompt:  joker walking down the street in a red suit and purple gloves, photorealistic octane 3d render, as action figures, full body photoshoot, on the runway, hottoys, 2 0 2 2 photo, high-quality photo, red yellow, with highly detailed, cosplay photo, sci - fi -
### Phase Encoding ###
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### Phase 1 Decoding ###
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### Phase 2 Denoising ###
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 48%|████▊     | 19/40 [00:24<00:27,  1.29s/it]
 50%|█████     | 20/40 [00:25<00:25,  1.29s/it]
 52%|█████▎    | 21/40 [00:27<00:24,  1.29s/it]
 55%|█████▌    | 22/40 [00:28<00:23,  1.29s/it]
 57%|█████▊    | 23/40 [00:29<00:21,  1.29s/it]
 60%|██████    | 24/40 [00:30<00:20,  1.29s/it]
 62%|██████▎   | 25/40 [00:32<00:19,  1.29s/it]
 65%|██████▌   | 26/40 [00:33<00:18,  1.29s/it]
 68%|██████▊   | 27/40 [00:34<00:16,  1.29s/it]
 70%|███████   | 28/40 [00:36<00:15,  1.29s/it]
 72%|███████▎  | 29/40 [00:37<00:14,  1.29s/it]
 75%|███████▌  | 30/40 [00:38<00:12,  1.29s/it]
 78%|███████▊  | 31/40 [00:39<00:11,  1.29s/it]
 80%|████████  | 32/40 [00:41<00:10,  1.29s/it]
 82%|████████▎ | 33/40 [00:42<00:09,  1.29s/it]
 85%|████████▌ | 34/40 [00:43<00:07,  1.29s/it]
 88%|████████▊ | 35/40 [00:45<00:06,  1.29s/it]
 90%|█████████ | 36/40 [00:46<00:05,  1.29s/it]
 92%|█████████▎| 37/40 [00:47<00:03,  1.29s/it]
 95%|█████████▌| 38/40 [00:48<00:02,  1.29s/it]
 98%|█████████▊| 39/40 [00:50<00:01,  1.29s/it]
### Phase 2 Decoding ###
100%|██████████| 40/40 [00:51<00:00,  1.29s/it]
100%|██████████| 40/40 [00:52<00:00,  1.31s/it]

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lucataco / demofusion-enhance

Prediction

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Output

Prediction

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Output

Prediction

Input

Output

Prediction

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Output

Prediction

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Output

Logs (yyxfu7lb62k5itmg6acv7dpjae)

Logs (futbmp3bunseptqkhsqozyzodu)

Logs (xuvor4dbpdflrg7g67gz3wjozy)

Logs (uvz2uflbsyozfak6i5n6em4irq)

Logs (v4mpr4tb7s4wyj37qbgc3go3me)