lucataco/pixart-sigma-900m:c9e6b6f8 – Run with an API on Replicate

Version

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lucataco /pixart-sigma-900m:c9e6b6f8

Input

prompt

string

Shift + Return to add a new line

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, grainycinematic 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

Input prompt

Default: "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"

negative_prompt

string

Shift + Return to add a new line

Input negative prompt

Default: ""

width

integer

Width of output image

Default: 1024

height

integer

Height of output image

Default: 1024

guidance_scale

number

(minimum: 1, maximum: 50)

Classifier-free guidance

Default: 3

num_inference_steps

integer

(minimum: 1, maximum: 100)

Number of denoising steps

Default: 20

seed

integer

Random seed. Leave blank to randomize the seed

Run this model in Node.js with one line of code:

npx create-replicate --model=lucataco/pixart-sigma-900m

or set up a project from scratch

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/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
    }
  }
);
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/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.

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/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": "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.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/lucataco/pixart-sigma-900m@sha256:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5 \
  -i 'width=1024' \
  -i 'height=1024' \
  -i '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"' \
  -i 'guidance_scale=5' \
  -i 'negative_prompt="worst, artifacts, deformed, distorted "' \
  -i 'num_inference_steps=20'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/lucataco/pixart-sigma-900m@sha256:c9e6b6f85c8ef629e088031cb85d9918c0cfdc3a11c8a9fb4ca3c16b78a8f9d5
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "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
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

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

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