dimcel / Hugging-Face-Playground

A simple Playground of Hugging Face API

Playground Overview

Here, you'll discover a diverse array of notebooks encompassing various tasks. These tasks range from image detection and depth perception to a simplistic chatbox implementation. Each notebook harnesses the power of Hugging Face's convenient API to streamline the process and enhance productivity.

Tasks Covered:

• Image Detection: Explore techniques and methodologies for detecting objects within images.
• Depth Detection: Dive into the realm of depth perception, uncovering methods to gauge distances in images.
  (Additional information available inside...)
• Simple Chatbox: Experience the creation of a basic chatbox, demonstrating the integration of language processing capabilities.

Additional Features:

• Gradio Integration: Most of the notebooks include a simple API for running on the web, built with Gradio. This allows for easy deployment and interaction with the models in a user-friendly interface.
• Focus on Hugging Face: This repository showcases the strength of Hugging Face and the ease of fine-tuning and running machine learning models. Explore the notebooks to witness firsthand the versatility and accessibility of Hugging Face's tools.

How to Run:

1. Set Up Virtual Environment: Before running the notebooks, it's recommended to create a virtual environment to isolate dependencies. You can do so by executing the following commands:

   # Create a virtual environment
   python -m venv myenv
   
   # Activate the virtual environment
   source myenv/bin/activate

2. Install Dependencies: Once the virtual environment is activated, install all necessary dependencies by executing:

   pip install -r requirements.txt

3. Run Notebooks: With the dependencies installed, you're ready to explore the notebooks! Open them in your preferred environment and start experimenting.