Credit to Gustavosta on Hugging Face for model

Based on Gustavosta's app.py script used for his Hugging Face Spaces. This is a trimmed and simplified implementation intended for running locally directly with python or via notebook

Requirements:

- Python 3.4 or higher
- Git-LFS 
- (Linux): python pip, tkinter
	- Tested on:
	- arch based: pacman -S python-pip tk
	- ubuntu 22.04 based: apt install python3-pip python3-tk

Recommended:

Use of virtual environments via venv or conda
- Included script files implement venv during install

How to use:

Scripts

- (Windows) Seperate batch files for python, jupyter, and colab local runtime
- (Linux) Single batch script with launch arguments
	- [no arguments] installs base requirements and launches normally
	- [ --jupyter ] installs base/jupyter requirements, launches notebook in browser
	- [ --colab ] installs base/jupyter requirements, allows local runtime from Google Colab

Python

- From terminal use " pip install -r requirements.txt " to grab dependencies
- Run python MagicPrompt.py
- Visit localhost:8088 in browser (substitute 'localhost' with devices ip address if run remotely)

Jupyter Notebook

- From terminal use " pip install -r notebook-requirements.txt " to grab dependencies
- Run " jupyter notebook MagicPrompt.ipynb "

Google Colab

- Visit https://colab.research.google.com
- Choose Upload tab
- Browse to file " MagicPrompt.ipynb "

- ***  Using Google's free servers: ***
- Just click connect in top right
- Use Runtime menu to run all

- ***  For local runtime:  ***
- From terminal use " pip install -r notebook-requirements.txt " to grab dependencies
- Run " jupyter notebook --no-browser --NotebookApp.allow_origin="https://colab.research.google.com" --port=8888 --NotebookApp.port_retries=0 "
- Copy URL containing token (e.g. http://localhost:8888/?token=5bbec....)
- In Colab, use dropdown next to connect and select 'Connect to a local runtime'
- Paste URL into the 'Backend URL' box and click connect
- Use Runtime menu to run all

From original README.md

This is a model from the MagicPrompt series of models, which are GPT-2 models intended to generate prompt texts for imaging AIs, in this case: Stable Diffusion. This model was trained with 150,000 steps and a set of about 80,000 data filtered and extracted from the image finder for Stable Diffusion: "Lexica.art". It was a little difficult to extract the data, since the search engine still doesn't have a public API without being protected by cloudflare, but if you want to take a look at the original dataset, you can have a look here: datasets/Gustavosta/Stable-Diffusion-Prompts. If you want to test the model with a demo, you can go to: "spaces/Gustavosta/MagicPrompt-Stable-Diffusion".

Changes from 'Spaces' app.py

• Model is saved to local folder allowing for offline use
• Colab-style notebook file for easy editing and use of gradio's in line interface
• Enabled gradio flagging feature, allows saving of prompt to log.csv
• Trimmed code by switching gradio's '.interface()' to '.interface.from_pipeline'
  • This was done to simplify code and prevent log.csv from filling with unwanted prompts
  • Likely going to change once I better learn python and the options of the transformers library
• Added requirements.txt for quick terminal deployment via pip
• Also added a seperate notebook-requirements.txt for use with jupyter notebook
• Changed port from gradio's standard to allow running at the same time as another gradio interface (e.g. Automatic1111's WebUI using default ports)
• Changed listening address from '127.0.0.1' (local host only) to '0.0.0.0' (network wide)
  • allows for access from other devices, useful for deployment on headless server
• Removed use of ideas.txt for examples
  • While some would consider it a nice addition, I find no value for my use case
• Added a favicon 🤗

Planned

• Add gradio options to test transformers temperature setting
• Add gradio options to test transformers beam search
• Add gradio options to select number of return sequences
• Add gradio option for random seed selection
• Add gradio tab for log.csv entries
• Consolidate .bat files into single file with launch args
• Add launch args for port selection

Pull requests welcome! I have no former python, and minimal scripting, experience.

This was intended as a learning project to get into python.

💻 You can see other MagicPrompt models:

• For Dall-E 2: Gustavosta/MagicPrompt-Dalle
• For Midjourney: Gustavosta/MagicPrompt-Midourney [⚠️ In progress]
• MagicPrompt full: Gustavosta/MagicPrompt [⚠️ In progress]

⚖️ Licence:

MIT

When using this model, please credit: Gustavosta

Thanks for reading this far! :)