cjwbw/future-diffusion – Run with an API on Replicate

cjwbw / future-diffusion

Finte-tuned Stable Diffusion on high quality 3D images with a futuristic Sci-Fi theme

Cold

Public
5.5K runs
T4

Run with an API

Playground API Examples README Versions

Input

prompt

string

Shift + Return to add a new line

Input prompt

Default: "future style Iron Man"

negative_prompt

string

Shift + Return to add a new line

The prompt or prompts not to guide the image generation (what you do not want to see in the generation). Ignored when not using guidance.

width

integer

Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 512

height

integer

Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 512

num_outputs

integer

Number of images to output

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 20

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7

scheduler

string

Choose a scheduler.

Default: "K_EULER_ANCESTRAL"

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=cjwbw/future-diffusion

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

const output = await replicate.run(
  "cjwbw/future-diffusion:b5c46a3b3f0db2a154d4be534ba7758caded970b748a2e26e6d02e9b3bd7da2a",
  {
    input: {
      width: 512,
      height: 704,
      prompt: "future style Iron Man",
      scheduler: "K_EULER_ANCESTRAL",
      num_outputs: 1,
      guidance_scale: 7,
      negative_prompt: "duplicate heads bad anatomy",
      num_inference_steps: 20
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

output = replicate.run(
    "cjwbw/future-diffusion:b5c46a3b3f0db2a154d4be534ba7758caded970b748a2e26e6d02e9b3bd7da2a",
    input={
        "width": 512,
        "height": 704,
        "prompt": "future style Iron Man",
        "scheduler": "K_EULER_ANCESTRAL",
        "num_outputs": 1,
        "guidance_scale": 7,
        "negative_prompt": "duplicate heads bad anatomy",
        "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/future-diffusion 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": "b5c46a3b3f0db2a154d4be534ba7758caded970b748a2e26e6d02e9b3bd7da2a",
    "input": {
      "width": 512,
      "height": 704,
      "prompt": "future style Iron Man",
      "scheduler": "K_EULER_ANCESTRAL",
      "num_outputs": 1,
      "guidance_scale": 7,
      "negative_prompt": "duplicate heads bad anatomy",
      "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": "2023-01-08T02:09:52.435152Z",
  "created_at": "2023-01-08T02:09:37.121018Z",
  "data_removed": false,
  "error": null,
  "id": "lg5lfuxrmrhhfarybk5phtzp4e",
  "input": {
    "width": 512,
    "height": "704",
    "prompt": "future style Iron Man",
    "scheduler": "K_EULER_ANCESTRAL",
    "num_outputs": 1,
    "guidance_scale": 7,
    "negative_prompt": "duplicate heads bad anatomy",
    "num_inference_steps": 20
  },
  "logs": "Using seed: 58006\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:13,  1.40it/s]\n 10%|█         | 2/20 [00:01<00:12,  1.41it/s]\n 15%|█▌        | 3/20 [00:02<00:12,  1.42it/s]\n 20%|██        | 4/20 [00:02<00:11,  1.41it/s]\n 25%|██▌       | 5/20 [00:03<00:10,  1.41it/s]\n 30%|███       | 6/20 [00:04<00:09,  1.41it/s]\n 35%|███▌      | 7/20 [00:04<00:09,  1.41it/s]\n 40%|████      | 8/20 [00:05<00:08,  1.41it/s]\n 45%|████▌     | 9/20 [00:06<00:07,  1.41it/s]\n 50%|█████     | 10/20 [00:07<00:07,  1.41it/s]\n 55%|█████▌    | 11/20 [00:07<00:06,  1.41it/s]\n 60%|██████    | 12/20 [00:08<00:05,  1.41it/s]\n 65%|██████▌   | 13/20 [00:09<00:04,  1.41it/s]\n 70%|███████   | 14/20 [00:09<00:04,  1.41it/s]\n 75%|███████▌  | 15/20 [00:10<00:03,  1.41it/s]\n 80%|████████  | 16/20 [00:11<00:02,  1.41it/s]\n 85%|████████▌ | 17/20 [00:12<00:02,  1.41it/s]\n 90%|█████████ | 18/20 [00:12<00:01,  1.41it/s]\n 95%|█████████▌| 19/20 [00:13<00:00,  1.41it/s]\n100%|██████████| 20/20 [00:14<00:00,  1.41it/s]\n100%|██████████| 20/20 [00:14<00:00,  1.41it/s]",
  "metrics": {
    "predict_time": 15.274834,
    "total_time": 15.314134
  },
  "output": [
    "https://replicate.delivery/pbxt/brazk2O1f6xpCSqbEmc59fyLkSsB3cOaI0M2aaaHeo0gf1HBB/out-0.png"
  ],
  "started_at": "2023-01-08T02:09:37.160318Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/lg5lfuxrmrhhfarybk5phtzp4e",
    "cancel": "https://api.replicate.com/v1/predictions/lg5lfuxrmrhhfarybk5phtzp4e/cancel"
  },
  "version": "b5c46a3b3f0db2a154d4be534ba7758caded970b748a2e26e6d02e9b3bd7da2a"
}

Generated in

15.3 seconds

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Examples

View more examples

Run time and cost

This model costs approximately $0.038 to run on Replicate, or 26 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 3 minutes. The predict time for this model varies significantly based on the inputs.

Readme

model weights: https://huggingface.co/nitrosocke/Future-Diffusion

Future Diffusion

This is the fine-tuned Stable Diffusion 2.0 model trained on high quality 3D images with a futuristic Sci-Fi theme. Use the tokens
future style
in your prompts for the effect. Trained on Stability.ai’s Stable Diffusion 2.0 Base with 512x512 resolution.

If you enjoy my work and want to test new models before release, please consider supporting me

Disclaimer: The SD 2.0 model is just over 24h old at this point and we still need to figure out how it works exactly. Please view this as an early prototype and experiment with the model.

Characters rendered with the model: Characters Samples Cars and Animals rendered with the model: Misc. Samples Landscapes rendered with the model: Landscape 1

License

This model is open access and available to all, with a CreativeML Open RAIL++-M License further specifying rights and usage. Please read the full license here