Welcome to Gradio Masterclass! 🚀 This repository is dedicated to teaching Gradio, an open-source Python library that makes it easy to build and share machine learning applications with a simple UI. Whether you're a beginner or an experienced ML practitioner, this masterclass will help you understand and implement Gradio effectively.
This repository covers:
- 📖 Introduction to Gradio
- 🛠 Building Interactive UIs for ML Models
- 🔄 Gradio Components & Customization
- 🚀 Deploying Gradio Apps
- 🏗 Advanced Use Cases
Ensure you have Python 3.7+ installed. Clone the repository and install dependencies:
git clone https://github.com/saadsalmanakram/Gradio-Masterclass.git
cd Gradio-Masterclass
pip install -r requirements.txt
Or install Gradio directly:
pip install gradio
Create a simple app.py
file:
import gradio as gr
def greet(name):
return f"Hello, {name}! Welcome to Gradio Masterclass!"
demo = gr.Interface(fn=greet, inputs="text", outputs="text")
demo.launch()
Run the script:
python app.py
You’ll see a link to an interactive UI! 🎉
- Basics of Gradio
- Why use Gradio for ML applications?
gr.Interface
gr.Blocks
gradio.inputs
&gradio.outputs
- Deploying NLP models
- Image classification demos
- Audio processing with Gradio
- Changing themes and layouts
- Adding custom CSS
- Using JavaScript callbacks
- Hosting on Hugging Face Spaces
- Deploying with Flask/FastAPI
- Using Docker for deployment
✅ Image Classification - Deploying a ResNet model with Gradio
✅ Chatbot with Hugging Face API - Using Gradio for chatbot UI
✅ QR Code Generator - Interactive QR code generation with qrcode
library
We welcome contributions! 🚀 To contribute:
- Fork the repository
- Create a new branch (
feature-xyz
) - Commit your changes
- Open a Pull Request (PR)
This project is licensed under the MIT License.
For queries, reach out to me on:
- GitHub: Saad Salman Akram
- LinkedIn: Saad Salman Akram
- Email: [email protected]
Happy Coding! 🚀