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https://github.com/cma-pio/super-duper-parakeet
text-to-picture
https://github.com/cma-pio/super-duper-parakeet
cuda diffusion-models pytorch
Last synced: 3 months ago
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text-to-picture
- Host: GitHub
- URL: https://github.com/cma-pio/super-duper-parakeet
- Owner: cma-pio
- Created: 2024-09-19T04:58:17.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-09-23T07:17:04.000Z (5 months ago)
- Last Synced: 2024-11-19T23:29:41.239Z (3 months ago)
- Topics: cuda, diffusion-models, pytorch
- Language: Python
- Homepage:
- Size: 6.84 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Local Image Generation with Diffusion Models
This project allows users to generate images interactively based on text prompts using a Stable Diffusion model. The model is powered by Hugging Face's `diffusers` library and runs in a local environment.
https://github.com/user-attachments/assets/8b41d41a-f73e-488a-9118-409e61540e0a
## Prerequisites
Before you run this project, make sure to have the following installed:
- Python 3.10+
- Virtual environment (e.g., `venv`)
- Hugging Face account
- Access to the Stable Diffusion model from Hugging Face
## Setup
1. **Clone the repository:**
```bash
git clone this repository
cd to the folder
```
2. **Create and activate a virtual environment:**
```bash
python -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
```
3. **Install the required dependencies:**
```bash
pip install -r requirements.txt
```
4. **Login to Hugging Face:**
This project uses the Stable Diffusion model from Hugging Face. You must log in to Hugging Face CLI with your access token before running the project.
- Apply for access to the Stable Diffusion 2.1 model at [Hugging Face's model page](https://huggingface.co/stabilityai/stable-diffusion-2-1).
- After gaining access, log in to Hugging Face from the terminal:
```bash
huggingface-cli login
```
This will prompt you to enter your access token, which you can find on your Hugging Face account page.
5. **Run the Streamlit App:**
After logging in, you can start the Streamlit app by running the following command:
```bash
streamlit run app.py
```
## Usage
1. Enter a prompt in the text box.
2. Click the "Generate Image" button to create a new image based on your prompt.
3. You can download the generated image by clicking the "Download Image" button.
## Logs
All runtime logs are saved in the `logs/` directory. They include information about model loading, image generation, and any errors encountered during runtime.
---
This will ensure users know to log in via the CLI before running your project.