cjwbw/pixart-sigma:dd378305 – Run with an API on Replicate

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cjwbw /pixart-sigma:dd378305

Playground API

Input

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

npx create-replicate --model=cjwbw/pixart-sigma

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

const output = await replicate.run(
  "cjwbw/pixart-sigma:dd378305882101b9be6ade3af645c36337f5050da8819f173f15ec4ad1210067",
  {
    input: {
      prompt: "Body shot, a French woman, Photography, French Streets background, backlight, rim light, Fujifilm.",
      guidance_scale: 4.5,
      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

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

output = replicate.run(
    "cjwbw/pixart-sigma:dd378305882101b9be6ade3af645c36337f5050da8819f173f15ec4ad1210067",
    input={
        "prompt": "Body shot, a French woman, Photography, French Streets background, backlight, rim light, Fujifilm.",
        "guidance_scale": 4.5,
        "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 cjwbw/pixart-sigma 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": "cjwbw/pixart-sigma:dd378305882101b9be6ade3af645c36337f5050da8819f173f15ec4ad1210067",
    "input": {
      "prompt": "Body shot, a French woman, Photography, French Streets background, backlight, rim light, Fujifilm.",
      "guidance_scale": 4.5,
      "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/chenxwh/pixart-sigma@sha256:dd378305882101b9be6ade3af645c36337f5050da8819f173f15ec4ad1210067 \
  -i 'prompt="Body shot, a French woman, Photography, French Streets background, backlight, rim light, Fujifilm."' \
  -i 'guidance_scale=4.5' \
  -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/chenxwh/pixart-sigma@sha256:dd378305882101b9be6ade3af645c36337f5050da8819f173f15ec4ad1210067
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "prompt": "Body shot, a French woman, Photography, French Streets background, backlight, rim light, Fujifilm.",
      "guidance_scale": 4.5,
      "num_inference_steps": 20
    }
  }' \
  http://localhost:5000/predictions

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

Output

{
  "completed_at": "2024-04-12T12:29:14.631474Z",
  "created_at": "2024-04-12T12:28:49.272000Z",
  "data_removed": false,
  "error": null,
  "id": "q5eebdscz1rgp0cet948dvzv0m",
  "input": {
    "prompt": "Body shot, a French woman, Photography, French Streets background, backlight, rim light, Fujifilm.",
    "guidance_scale": 4.5,
    "num_inference_steps": 20
  },
  "logs": "Using seed: 29560\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 [00:01<00:21,  1.12s/it]\n 10%|█         | 2/20 [00:02<00:20,  1.12s/it]\n 15%|█▌        | 3/20 [00:03<00:19,  1.12s/it]\n 20%|██        | 4/20 [00:04<00:17,  1.12s/it]\n 25%|██▌       | 5/20 [00:05<00:16,  1.12s/it]\n 30%|███       | 6/20 [00:06<00:15,  1.12s/it]\n 35%|███▌      | 7/20 [00:07<00:14,  1.12s/it]\n 40%|████      | 8/20 [00:08<00:13,  1.13s/it]\n 45%|████▌     | 9/20 [00:10<00:12,  1.13s/it]\n 50%|█████     | 10/20 [00:11<00:11,  1.13s/it]\n 55%|█████▌    | 11/20 [00:12<00:10,  1.13s/it]\n 60%|██████    | 12/20 [00:13<00:09,  1.13s/it]\n 65%|██████▌   | 13/20 [00:14<00:07,  1.13s/it]\n 70%|███████   | 14/20 [00:15<00:06,  1.13s/it]\n 75%|███████▌  | 15/20 [00:16<00:05,  1.13s/it]\n 80%|████████  | 16/20 [00:18<00:04,  1.13s/it]\n 85%|████████▌ | 17/20 [00:19<00:03,  1.13s/it]\n 90%|█████████ | 18/20 [00:20<00:02,  1.13s/it]\n 95%|█████████▌| 19/20 [00:21<00:01,  1.14s/it]\n100%|██████████| 20/20 [00:22<00:00,  1.14s/it]\n100%|██████████| 20/20 [00:22<00:00,  1.13s/it]",
  "metrics": {
    "predict_time": 25.322103,
    "total_time": 25.359474
  },
  "output": "https://replicate.delivery/pbxt/0AeaXnG6xTSOQ6qr2RDcfwuwMfwxqeNqtuujhPWW5cwnx2mKB/out.png",
  "started_at": "2024-04-12T12:28:49.309371Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/q5eebdscz1rgp0cet948dvzv0m",
    "cancel": "https://api.replicate.com/v1/predictions/q5eebdscz1rgp0cet948dvzv0m/cancel"
  },
  "version": "dd378305882101b9be6ade3af645c36337f5050da8819f173f15ec4ad1210067"
}

Generated in

25.3 seconds

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