Input

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

npx create-replicate --model=cjwbw/distilgpt2-stable-diffusion-v2

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/distilgpt2-stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/distilgpt2-stable-diffusion-v2:d53a494f0f1f4130d39cbe574c25d267910e1fce4e7f4b34fe15f22976aed332",
  {
    input: {
      top_k: 50,
      prompt: "a cat sitting",
      max_length: 80,
      temperature: 0.9,
      repitition_penalty: 1.2,
      num_return_sequences: 5
    }
  }
);

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 cjwbw/distilgpt2-stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/distilgpt2-stable-diffusion-v2:d53a494f0f1f4130d39cbe574c25d267910e1fce4e7f4b34fe15f22976aed332",
    input={
        "top_k": 50,
        "prompt": "a cat sitting",
        "max_length": 80,
        "temperature": 0.9,
        "repitition_penalty": 1.2,
        "num_return_sequences": 5
    }
)
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/distilgpt2-stable-diffusion-v2 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": "d53a494f0f1f4130d39cbe574c25d267910e1fce4e7f4b34fe15f22976aed332",
    "input": {
      "top_k": 50,
      "prompt": "a cat sitting",
      "max_length": 80,
      "temperature": 0.9,
      "repitition_penalty": 1.2,
      "num_return_sequences": 5
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

a cat sitting in a coffee shop on the moon surface, closeup photo-real delicate ceramic porcelain sculpture of an ornate detailed mermaid as emma watson by rafael and lee madgwick with intricate white flowery details :: clockwork orange color scheme:: full body composition: volumetric lightsand foggy atmosphere. epic elegant pose!!! anime lightning!! cinematic shot a cat sitting on a bench in the park, beautiful digital art by greg rutkowski and thomas kinkade with ambient lighting. highly detailed painting of an orange colored fox standing up next to him holding white fluffy dog that is looking at it from bay windowsill while wearing headphones!!! trending artwork 4k hd render very coherent symmetrical perfect anatomy portrait!! smooth sharp focus illustration highlights light a cat sitting on a table drinking beer from an orange mushroom in the desert. digital art, trending at pixiv's - n 9 5 4 0 s horror movie still by dan mumford and thomas kinkade 8 3 2 w 7 6 hq sharp contrast intricate details award winning detailed octane render unreal engine beautiful colors masterpiece many cake foggy like ghibliak tachik a cat sitting in a chair, digital art by edward hopper and james gilleard painting highly detailed trending on arstation station cinematic lighting close up shot photograph detail cyberpunk 2077 colors octane render excellent composition dramatic studio action scene aesthetic 8k ultra hd resolution smooth sharp focus oil painted with colored paint splashes of canvas concept design matte drawing stylized vegetation forest fisheye a cat sitting on a chair reading an old book, digital art in the style of pixar trending by james gurney 1 0 8 7 studio lighting product photography highly detailed realism hd shadows depth 3 2 k. 5 d ue 6 as background bokeh sigma f / 4 - 50 mm nikon z 9 canon eos r | ghost shipwra during golden

{
  "completed_at": "2023-02-02T17:19:31.999702Z",
  "created_at": "2023-02-02T17:18:24.049294Z",
  "data_removed": false,
  "error": null,
  "id": "7xvtwwdgzzfilhhtlkw5ojum24",
  "input": {
    "top_k": 50,
    "prompt": "a cat sitting",
    "max_length": 80,
    "temperature": 0.9,
    "repitition_penalty": 1.2,
    "num_return_sequences": 5
  },
  "logs": null,
  "metrics": {
    "predict_time": 5.178619,
    "total_time": 67.950408
  },
  "output": "a cat sitting in a coffee shop on the moon surface, closeup photo-real delicate ceramic porcelain sculpture of an ornate detailed mermaid as emma watson by rafael and lee madgwick with intricate white flowery details :: clockwork orange color scheme:: full body composition: volumetric lightsand foggy atmosphere. epic elegant pose!!! anime lightning!! cinematic shot\n\na cat sitting on a bench in the park, beautiful digital art by greg rutkowski and thomas kinkade with ambient lighting. highly detailed painting of an orange colored fox standing up next to him holding white fluffy dog that is looking at it from bay windowsill while wearing headphones!!! trending artwork 4k hd render very coherent symmetrical perfect anatomy portrait!! smooth sharp focus illustration highlights light\n\na cat sitting on a table drinking beer from an orange mushroom in the desert. digital art, trending at pixiv's - n 9 5 4 0 s horror movie still by dan mumford and thomas kinkade 8 3 2 w 7 6 hq sharp contrast intricate details award winning detailed octane render unreal engine beautiful colors masterpiece many cake foggy like ghibliak tachik\n\na cat sitting in a chair, digital art by edward hopper and james gilleard painting highly detailed trending on arstation station cinematic lighting close up shot photograph detail cyberpunk 2077 colors octane render excellent composition dramatic studio action scene aesthetic 8k ultra hd resolution smooth sharp focus oil painted with colored paint splashes of canvas concept design matte drawing stylized vegetation forest fisheye\n\na cat sitting on a chair reading an old book, digital art in the style of pixar trending by james gurney 1 0 8 7 studio lighting product photography highly detailed realism hd shadows depth 3 2 k. 5 d ue 6 as background bokeh sigma f / 4 - 50 mm nikon z 9 canon eos r | ghost shipwra during golden\n\n",
  "started_at": "2023-02-02T17:19:26.821083Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/7xvtwwdgzzfilhhtlkw5ojum24",
    "cancel": "https://api.replicate.com/v1/predictions/7xvtwwdgzzfilhhtlkw5ojum24/cancel"
  },
  "version": "d53a494f0f1f4130d39cbe574c25d267910e1fce4e7f4b34fe15f22976aed332"
}

Generated in

5.2 seconds

Tweak it Report

Run time and cost

This model costs approximately $0.020 to run on Replicate, or 50 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 90 seconds. The predict time for this model varies significantly based on the inputs.

Readme

weights from: https://huggingface.co/FredZhang7/distilgpt2-stable-diffusion-v2 cog implementation: https://github.com/chenxwh/cog-themed-diffusion/tree/distilgpt2

DistilGPT2 Stable Diffusion V2

This model was trained on 2,470,000 descriptive stable diffusion prompts on the FredZhang7/distilgpt2-stable-diffusion checkpoint for another 4,270,000 steps.

Compared to other prompt generation models using GPT2, this one runs with 50% faster forwardpropagation and 40% less disk space & RAM.

Major improvements from v1 are: - 25% more variations - faster and more fluent prompt generation - cleaned training data * removed prompts that generate images with nsfw scores > 0.5 * removed duplicates, including prompts that differ by capitalization and punctuations * removed punctuations at random places * removed prompts shorter than 15 characters