lucataco / pixart-sigma-900m

width: 1024
height: 1024
prompt: high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette
guidance_scale: 3
negative_prompt
num_inference_steps: 20

{
  "width": 1024,
  "height": 1024,
  "prompt": "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette",
  "guidance_scale": 3,
  "negative_prompt": "",
  "num_inference_steps": 20
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette",
      guidance_scale: 3,
      negative_prompt: "",
      num_inference_steps: 20
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette",
        "guidance_scale": 3,
        "negative_prompt": "",
        "num_inference_steps": 20
    }
)
print(output)

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette",
      "guidance_scale": 3,
      "negative_prompt": "",
      "num_inference_steps": 20
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-07-13T03:47:15.757661Z",
  "created_at": "2024-07-13T03:43:43.350000Z",
  "data_removed": false,
  "error": null,
  "id": "bde5w23yysrgm0cgn8r8j6n3wr",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "high quality pixel art, a pixel art silhouette of an anime space-themed girl in a space-punk steampunk style, lying in her bed by the window of a spaceship, smoking, with a rustic feel. The image should embody epic portraiture and double exposure, featuring an isolated landscape visible through the window. The colors should primarily be dynamic and action-packed, with a strong use of negative space. The entire artwork should be in pixel art style, emphasizing the characters shape and set against a white background. Silhouette",
    "guidance_scale": 3,
    "negative_prompt": "",
    "num_inference_steps": 20
  },
  "logs": "Using seed: 16147\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:07,  2.57it/s]\n 15%|█▌        | 3/20 [00:00<00:04,  4.21it/s]\n 20%|██        | 4/20 [00:01<00:04,  3.92it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  3.75it/s]\n 30%|███       | 6/20 [00:01<00:03,  3.66it/s]\n 35%|███▌      | 7/20 [00:01<00:03,  3.59it/s]\n 40%|████      | 8/20 [00:02<00:03,  3.55it/s]\n 45%|████▌     | 9/20 [00:02<00:03,  3.52it/s]\n 50%|█████     | 10/20 [00:02<00:02,  3.50it/s]\n 55%|█████▌    | 11/20 [00:03<00:02,  3.48it/s]\n 60%|██████    | 12/20 [00:03<00:02,  3.47it/s]\n 65%|██████▌   | 13/20 [00:03<00:02,  3.47it/s]\n 70%|███████   | 14/20 [00:03<00:01,  3.46it/s]\n 75%|███████▌  | 15/20 [00:04<00:01,  3.46it/s]\n 80%|████████  | 16/20 [00:04<00:01,  3.45it/s]\n 85%|████████▌ | 17/20 [00:04<00:00,  3.45it/s]\n 90%|█████████ | 18/20 [00:05<00:00,  3.45it/s]\n 95%|█████████▌| 19/20 [00:05<00:00,  3.45it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.45it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.52it/s]",
  "metrics": {
    "predict_time": 8.002685324,
    "total_time": 212.407661
  },
  "output": "https://replicate.delivery/pbxt/slwBMxLHvjqOHJZZmIITSryscVBFEMTHIpBccxW99QkwqejJA/output.jpg",
  "started_at": "2024-07-13T03:47:07.754976Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/bde5w23yysrgm0cgn8r8j6n3wr",
    "cancel": "https://api.replicate.com/v1/predictions/bde5w23yysrgm0cgn8r8j6n3wr/cancel"
  },
  "version": "c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5"
}

Generated in

8.0 seconds

Tweak it Share Report

Prediction

lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5

Model

lucataco/pixart-sigma-900m:c9e6b6f8

wb5d0yvsynrgm0cgn8t9n9hs14

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

7.4s

Created

11 months ago

Input

width: 1024
height: 1024
prompt: black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed
guidance_scale: 5
negative_prompt
num_inference_steps: 20

{
  "width": 1024,
  "height": 1024,
  "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed",
  "guidance_scale": 5,
  "negative_prompt": "",
  "num_inference_steps": 20
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed",
      guidance_scale: 5,
      negative_prompt: "",
      num_inference_steps: 20
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed",
        "guidance_scale": 5,
        "negative_prompt": "",
        "num_inference_steps": 20
    }
)
print(output)

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed",
      "guidance_scale": 5,
      "negative_prompt": "",
      "num_inference_steps": 20
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-07-13T03:48:11.639825Z",
  "created_at": "2024-07-13T03:48:04.213000Z",
  "data_removed": false,
  "error": null,
  "id": "wb5d0yvsynrgm0cgn8t9n9hs14",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed",
    "guidance_scale": 5,
    "negative_prompt": "",
    "num_inference_steps": 20
  },
  "logs": "Using seed: 23753\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:05,  3.44it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  4.71it/s]\n 20%|██        | 4/20 [00:00<00:03,  4.19it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  3.92it/s]\n 30%|███       | 6/20 [00:01<00:03,  3.76it/s]\n 35%|███▌      | 7/20 [00:01<00:03,  3.66it/s]\n 40%|████      | 8/20 [00:02<00:03,  3.59it/s]\n 45%|████▌     | 9/20 [00:02<00:03,  3.55it/s]\n 50%|█████     | 10/20 [00:02<00:02,  3.51it/s]\n 55%|█████▌    | 11/20 [00:02<00:02,  3.49it/s]\n 60%|██████    | 12/20 [00:03<00:02,  3.47it/s]\n 65%|██████▌   | 13/20 [00:03<00:02,  3.46it/s]\n 70%|███████   | 14/20 [00:03<00:01,  3.46it/s]\n 75%|███████▌  | 15/20 [00:04<00:01,  3.45it/s]\n 80%|████████  | 16/20 [00:04<00:01,  3.45it/s]\n 85%|████████▌ | 17/20 [00:04<00:00,  3.44it/s]\n 90%|█████████ | 18/20 [00:05<00:00,  3.44it/s]\n 95%|█████████▌| 19/20 [00:05<00:00,  3.44it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.44it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.57it/s]",
  "metrics": {
    "predict_time": 7.388063615,
    "total_time": 7.426825
  },
  "output": "https://replicate.delivery/pbxt/tRHyxYUqu8L5EpGajFP9MXB8ezSLQEFYpOrUueChzKp6r6HTA/output.jpg",
  "started_at": "2024-07-13T03:48:04.251762Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/wb5d0yvsynrgm0cgn8t9n9hs14",
    "cancel": "https://api.replicate.com/v1/predictions/wb5d0yvsynrgm0cgn8t9n9hs14/cancel"
  },
  "version": "c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5"
}

Generated in

7.4 seconds

Tweak it Share Report

Prediction

lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5

Model

lucataco/pixart-sigma-900m:c9e6b6f8

zwwjqrps95rgg0cgn8tvsrxg1c

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

7.5s

Created

11 months ago

Input

width: 1024
height: 1024
prompt: Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne dArc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd
guidance_scale: 5
negative_prompt: worst, artifacts, deformed, distorted
num_inference_steps: 20

{
  "width": 1024,
  "height": 1024,
  "prompt": "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne dArc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd",
  "guidance_scale": 5,
  "negative_prompt": "worst, artifacts, deformed, distorted ",
  "num_inference_steps": 20
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne dArc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd",
      guidance_scale: 5,
      negative_prompt: "worst, artifacts, deformed, distorted ",
      num_inference_steps: 20
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne dArc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd",
        "guidance_scale": 5,
        "negative_prompt": "worst, artifacts, deformed, distorted ",
        "num_inference_steps": 20
    }
)
print(output)

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne dArc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd",
      "guidance_scale": 5,
      "negative_prompt": "worst, artifacts, deformed, distorted ",
      "num_inference_steps": 20
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-07-13T03:49:41.637583Z",
  "created_at": "2024-07-13T03:49:34.153000Z",
  "data_removed": false,
  "error": null,
  "id": "zwwjqrps95rgg0cgn8tvsrxg1c",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass flowers, Stains, space grunge style, Jeanne dArc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd",
    "guidance_scale": 5,
    "negative_prompt": "worst, artifacts, deformed, distorted ",
    "num_inference_steps": 20
  },
  "logs": "Using seed: 43292\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:05,  3.43it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  4.68it/s]\n 20%|██        | 4/20 [00:00<00:03,  4.10it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  3.84it/s]\n 30%|███       | 6/20 [00:01<00:03,  3.70it/s]\n 35%|███▌      | 7/20 [00:01<00:03,  3.60it/s]\n 40%|████      | 8/20 [00:02<00:03,  3.55it/s]\n 45%|████▌     | 9/20 [00:02<00:03,  3.51it/s]\n 50%|█████     | 10/20 [00:02<00:02,  3.48it/s]\n 55%|█████▌    | 11/20 [00:03<00:02,  3.46it/s]\n 60%|██████    | 12/20 [00:03<00:02,  3.45it/s]\n 65%|██████▌   | 13/20 [00:03<00:02,  3.44it/s]\n 70%|███████   | 14/20 [00:03<00:01,  3.43it/s]\n 75%|███████▌  | 15/20 [00:04<00:01,  3.43it/s]\n 80%|████████  | 16/20 [00:04<00:01,  3.42it/s]\n 85%|████████▌ | 17/20 [00:04<00:00,  3.42it/s]\n 90%|█████████ | 18/20 [00:05<00:00,  3.41it/s]\n 95%|█████████▌| 19/20 [00:05<00:00,  3.41it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.42it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.54it/s]",
  "metrics": {
    "predict_time": 7.446382185,
    "total_time": 7.484583
  },
  "output": "https://replicate.delivery/pbxt/R3K2fhfEyXu5cElLLRrf1i0ZfROhPjSfCqSmFDqkAU3nqVfxE/output.jpg",
  "started_at": "2024-07-13T03:49:34.191201Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/zwwjqrps95rgg0cgn8tvsrxg1c",
    "cancel": "https://api.replicate.com/v1/predictions/zwwjqrps95rgg0cgn8tvsrxg1c/cancel"
  },
  "version": "c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5"
}

Generated in

7.5 seconds

Tweak it Share Report

Prediction

lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5

Model

lucataco/pixart-sigma-900m:c9e6b6f8

08k5rfh2cxrgm0cgn8vamjmraw

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

7.5s

Created

11 months ago

Input

width: 1024
height: 1024
prompt: cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy
guidance_scale: 5
negative_prompt: worst, artifacts, deformed, distorted
num_inference_steps: 20

{
  "width": 1024,
  "height": 1024,
  "prompt": "cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
  "guidance_scale": 5,
  "negative_prompt": "worst, artifacts, deformed, distorted ",
  "num_inference_steps": 20
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
      guidance_scale: 5,
      negative_prompt: "worst, artifacts, deformed, distorted ",
      num_inference_steps: 20
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
        "guidance_scale": 5,
        "negative_prompt": "worst, artifacts, deformed, distorted ",
        "num_inference_steps": 20
    }
)
print(output)

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
      "guidance_scale": 5,
      "negative_prompt": "worst, artifacts, deformed, distorted ",
      "num_inference_steps": 20
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-07-13T03:50:00.328102Z",
  "created_at": "2024-07-13T03:49:52.871000Z",
  "data_removed": false,
  "error": null,
  "id": "08k5rfh2cxrgm0cgn8vamjmraw",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
    "guidance_scale": 5,
    "negative_prompt": "worst, artifacts, deformed, distorted ",
    "num_inference_steps": 20
  },
  "logs": "Using seed: 28223\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:05,  3.44it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  4.71it/s]\n 20%|██        | 4/20 [00:00<00:03,  4.17it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  3.89it/s]\n 30%|███       | 6/20 [00:01<00:03,  3.73it/s]\n 35%|███▌      | 7/20 [00:01<00:03,  3.64it/s]\n 40%|████      | 8/20 [00:02<00:03,  3.56it/s]\n 45%|████▌     | 9/20 [00:02<00:03,  3.52it/s]\n 50%|█████     | 10/20 [00:02<00:02,  3.50it/s]\n 55%|█████▌    | 11/20 [00:02<00:02,  3.47it/s]\n 60%|██████    | 12/20 [00:03<00:02,  3.46it/s]\n 65%|██████▌   | 13/20 [00:03<00:02,  3.45it/s]\n 70%|███████   | 14/20 [00:03<00:01,  3.44it/s]\n 75%|███████▌  | 15/20 [00:04<00:01,  3.43it/s]\n 80%|████████  | 16/20 [00:04<00:01,  3.43it/s]\n 85%|████████▌ | 17/20 [00:04<00:00,  3.43it/s]\n 90%|█████████ | 18/20 [00:05<00:00,  3.42it/s]\n 95%|█████████▌| 19/20 [00:05<00:00,  3.42it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.43it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.56it/s]",
  "metrics": {
    "predict_time": 7.420112041,
    "total_time": 7.457102
  },
  "output": "https://replicate.delivery/pbxt/f6zMKKPFdd2gIqOwDCbkfURIbbQfeWHfjvXcRNimwu8eZrejJA/output.jpg",
  "started_at": "2024-07-13T03:49:52.907990Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/08k5rfh2cxrgm0cgn8vamjmraw",
    "cancel": "https://api.replicate.com/v1/predictions/08k5rfh2cxrgm0cgn8vamjmraw/cancel"
  },
  "version": "c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5"
}

Generated in

7.4 seconds

Tweak it Share Report

Prediction

lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5

Model

lucataco/pixart-sigma-900m:c9e6b6f8

emce305005rgm0cgn8v92mm5vg

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

7.4s

Created

11 months ago

Input

width: 1024
height: 1024
prompt: The image features an older man, a long white beard and mustache, He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy
guidance_scale: 5
negative_prompt: worst, artifacts, deformed, distorted
num_inference_steps: 20

{
  "width": 1024,
  "height": 1024,
  "prompt": "The image features an older man, a long white beard and mustache,  He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
  "guidance_scale": 5,
  "negative_prompt": "worst, artifacts, deformed, distorted ",
  "num_inference_steps": 20
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "The image features an older man, a long white beard and mustache,  He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
      guidance_scale: 5,
      negative_prompt: "worst, artifacts, deformed, distorted ",
      num_inference_steps: 20
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "The image features an older man, a long white beard and mustache,  He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
        "guidance_scale": 5,
        "negative_prompt": "worst, artifacts, deformed, distorted ",
        "num_inference_steps": 20
    }
)
print(output)

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "The image features an older man, a long white beard and mustache,  He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
      "guidance_scale": 5,
      "negative_prompt": "worst, artifacts, deformed, distorted ",
      "num_inference_steps": 20
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-07-13T03:50:32.443319Z",
  "created_at": "2024-07-13T03:50:25.025000Z",
  "data_removed": false,
  "error": null,
  "id": "emce305005rgm0cgn8v92mm5vg",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "The image features an older man, a long white beard and mustache,  He has a stern expression, giving the impression of a wise and experienced individual. The mans beard and mustache are prominent, adding to his distinguished appearance. The close-up shot of the mans face emphasizes his facial features and the intensity of his gaze.cinematic film still of Kodak Motion Picture Film (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
    "guidance_scale": 5,
    "negative_prompt": "worst, artifacts, deformed, distorted ",
    "num_inference_steps": 20
  },
  "logs": "Using seed: 58754\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:05,  3.43it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  4.69it/s]\n 20%|██        | 4/20 [00:00<00:03,  4.17it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  3.89it/s]\n 30%|███       | 6/20 [00:01<00:03,  3.73it/s]\n 35%|███▌      | 7/20 [00:01<00:03,  3.63it/s]\n 40%|████      | 8/20 [00:02<00:03,  3.56it/s]\n 45%|████▌     | 9/20 [00:02<00:03,  3.52it/s]\n 50%|█████     | 10/20 [00:02<00:02,  3.49it/s]\n 55%|█████▌    | 11/20 [00:02<00:02,  3.47it/s]\n 60%|██████    | 12/20 [00:03<00:02,  3.46it/s]\n 65%|██████▌   | 13/20 [00:03<00:02,  3.44it/s]\n 70%|███████   | 14/20 [00:03<00:01,  3.44it/s]\n 75%|███████▌  | 15/20 [00:04<00:01,  3.43it/s]\n 80%|████████  | 16/20 [00:04<00:01,  3.43it/s]\n 85%|████████▌ | 17/20 [00:04<00:00,  3.42it/s]\n 90%|█████████ | 18/20 [00:05<00:00,  3.42it/s]\n 95%|█████████▌| 19/20 [00:05<00:00,  3.42it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.42it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.55it/s]",
  "metrics": {
    "predict_time": 7.380652278,
    "total_time": 7.418319
  },
  "output": "https://replicate.delivery/pbxt/XZAb1lpMWGZ8AVFYqBsx1CQLSvXjL3bNNiYZEYk7KP7hrejJA/output.jpg",
  "started_at": "2024-07-13T03:50:25.062667Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/emce305005rgm0cgn8v92mm5vg",
    "cancel": "https://api.replicate.com/v1/predictions/emce305005rgm0cgn8v92mm5vg/cancel"
  },
  "version": "c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5"
}

Generated in

7.4 seconds

Tweak it Share Report

Prediction

lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5

Model

lucataco/pixart-sigma-900m:c9e6b6f8

8hatjkpr61rgp0cgn8v9wtp9rr

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

7.4s

Created

11 months ago

Input

width: 1024
height: 1024
prompt: anime girl
guidance_scale: 5
negative_prompt: worst, artifacts, deformed, distorted
num_inference_steps: 20

{
  "width": 1024,
  "height": 1024,
  "prompt": "anime girl",
  "guidance_scale": 5,
  "negative_prompt": "worst, artifacts, deformed, distorted ",
  "num_inference_steps": 20
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "anime girl",
      guidance_scale: 5,
      negative_prompt: "worst, artifacts, deformed, distorted ",
      num_inference_steps: 20
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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

Import the client:

import replicate

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "anime girl",
        "guidance_scale": 5,
        "negative_prompt": "worst, artifacts, deformed, distorted ",
        "num_inference_steps": 20
    }
)
print(output)

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

Run lucataco/pixart-sigma-900m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "lucataco/pixart-sigma-900m:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "anime girl",
      "guidance_scale": 5,
      "negative_prompt": "worst, artifacts, deformed, distorted ",
      "num_inference_steps": 20
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-07-13T03:50:46.829379Z",
  "created_at": "2024-07-13T03:50:39.408000Z",
  "data_removed": false,
  "error": null,
  "id": "8hatjkpr61rgp0cgn8v9wtp9rr",
  "input": {
    "width": 1024,
    "height": 1024,
    "prompt": "anime girl",
    "guidance_scale": 5,
    "negative_prompt": "worst, artifacts, deformed, distorted ",
    "num_inference_steps": 20
  },
  "logs": "Using seed: 12225\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\nSetting `clean_caption=True` requires the Beautiful Soup library but it was not found in your environment. You can install it with pip:\n`pip install beautifulsoup4`. Please note that you may need to restart your runtime after installation.\nSetting `clean_caption` to False...\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:05,  3.43it/s]\n 15%|█▌        | 3/20 [00:00<00:03,  4.69it/s]\n 20%|██        | 4/20 [00:00<00:03,  4.16it/s]\n 25%|██▌       | 5/20 [00:01<00:03,  3.88it/s]\n 30%|███       | 6/20 [00:01<00:03,  3.73it/s]\n 35%|███▌      | 7/20 [00:01<00:03,  3.63it/s]\n 40%|████      | 8/20 [00:02<00:03,  3.56it/s]\n 45%|████▌     | 9/20 [00:02<00:03,  3.52it/s]\n 50%|█████     | 10/20 [00:02<00:02,  3.49it/s]\n 55%|█████▌    | 11/20 [00:02<00:02,  3.47it/s]\n 60%|██████    | 12/20 [00:03<00:02,  3.45it/s]\n 65%|██████▌   | 13/20 [00:03<00:02,  3.44it/s]\n 70%|███████   | 14/20 [00:03<00:01,  3.44it/s]\n 75%|███████▌  | 15/20 [00:04<00:01,  3.43it/s]\n 80%|████████  | 16/20 [00:04<00:01,  3.43it/s]\n 85%|████████▌ | 17/20 [00:04<00:00,  3.42it/s]\n 90%|█████████ | 18/20 [00:05<00:00,  3.42it/s]\n 95%|█████████▌| 19/20 [00:05<00:00,  3.42it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.42it/s]\n100%|██████████| 20/20 [00:05<00:00,  3.55it/s]",
  "metrics": {
    "predict_time": 7.383248017,
    "total_time": 7.421379
  },
  "output": "https://replicate.delivery/pbxt/267Mj8JNgirLFZ2EExlapfLfzbrVqj706FCGM9AwJhMVu6HTA/output.jpg",
  "started_at": "2024-07-13T03:50:39.446131Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/8hatjkpr61rgp0cgn8v9wtp9rr",
    "cancel": "https://api.replicate.com/v1/predictions/8hatjkpr61rgp0cgn8v9wtp9rr/cancel"
  },
  "version": "c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5"
}

Generated in

7.4 seconds

Tweak it Share Report