README.md

---
title: TransformersPipelinePlayground
emoji: 💻
colorFrom: green
colorTo: indigo
sdk: gradio
sdk_version: 5.19.0
app_file: app.py
pinned: false
license: mit
---

## Transformers Pipeline Playground 🎡🤖

**Welcome to the Transformers Pipeline Playground!** This project provides an interactive interface to explore and experiment with various transformer models using Hugging Face’s transformers library. Whether you’re a seasoned NLP practitioner or just getting started, this playground offers a hands-on experience with state-of-the-art models.

[![PyPI version](https://badge.fury.io/py/my-python-package.svg)](https://pypi.org/project/my-python-package/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.9+](https://img.shields.io/badge/python-%3E=3.9-blue.svg)](https://www.python.org/downloads)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Python CI](https://github.com/canstralian/transformers-pipeline-playground/actions/workflows/ci.yml/badge.svg)](https://github.com/canstralian/My-Python-Project-Template/actions/workflows/ci.yml)

**Features** ✨
- Interactive Model Exploration: Load and test different transformer models directly in your browser.
- User-Friendly Interface: Utilizes Gradio to create an accessible web-based UI.
- Flexible Pipeline Selection: Choose from a variety of pipelines such as text generation, sentiment analysis, and more.

## Installation 🛠️

To set up the Transformers Pipeline Playground locally, follow these steps:
	1.	Clone the Repository:

git clone https://github.com/canstralian/transformers-pipeline-playground.git
cd transformers-pipeline-playground


	2.	Install Dependencies:
It’s recommended to use a virtual environment:

python3 -m venv env
source env/bin/activate  # On Windows, use `env\Scripts\activate`

Then, install the required packages:

pip install -r requirements.txt



## Usage 🚀

After installing the dependencies, you can launch the application with:

python app.py

This will start a local server. Open your browser and navigate to the displayed URL to access the interface.

How It Works 🧠

The application leverages Hugging Face’s transformers library to load pre-trained models and create pipelines for various NLP tasks. The user interface is built with Gradio, providing an easy way to interact with the models.

## Contributing 🤝

Contributions are welcome! If you have ideas for improvements or new features, feel free to open an issue or submit a pull request.

## License 📄

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

Note: Remember, with great transformer power comes great responsibility. Use the models ethically and consider the implications of their outputs.


Check out the configuration reference at https://huggingface.co./docs/hub/spaces-config-reference