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Canstralian/RedTeamAI-new

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App README

RedTeamAI New 👀

This Space is an example chatbot built using Gradio, huggingface_hub, and the Hugging Face Inference API. It demonstrates the integration of machine learning models with an interactive user interface.

Features

  • —Load and preprocess datasets from Kaggle or Hugging Face.
  • —Fine-tune and train models using transformers and datasets.
  • —Set up inference pipelines for real-time text generation.
  • —Deploy an interactive Gradio interface for user interaction.

How It Works

  1. 1.Data Processing: The application downloads datasets and preprocesses them for training.
  2. 2.Model Training: Fine-tunes a pre-trained model (e.g., GPT-2) using Hugging Face transformers.
  3. 3.Inference: Sets up a pipeline to generate text responses.
  4. 4.User Interaction: Launches a Gradio-based chatbot interface for users to interact with the trained model.

Quickstart

  1. 1.Clone this repository:
bash
   git clone https://huggingface.co/spaces/your-username/RedTeamAI-New
   cd RedTeamAI-New

	2.	Install the dependencies:

pip install -r requirements.txt


	3.	Run the application locally:

python app.py


	4.	Visit the Gradio app in your browser at http://localhost:7860.

Dependencies

This project uses the following libraries:
   •   gradio>=5.6.0
   •   transformers==4.40.0
   •   datasets==2.10.1
   •   huggingface_hub==0.22.2
   •   torch==2.1.0
   •   numpy==1.24.3
   •   pandas==2.0.3
   •   kaggle==1.5.13

Check requirements.txt for full details.

License

This project is licensed under the MIT License. See LICENSE for more details.

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