Building a custom AI chatbot from audio or text is easier than ever with tools like Whisper AI and Google’s T5 Flan model. Start by choosing your content—this could be a podcast, audiobook, or any written document. If it’s audio, use Whisper AI to convert it into accurate, readable text. Once you have the transcript, clean it up by removing filler words and formatting it into a Q&A style or structured dialogue. This will serve as the training data for your chatbot.
Next, head over to Hugging Face and fine-tune the T5 Flan model using your content. You’ll need to set up a Python environment, log in via the Hugging Face CLI, and upload your dataset. Once trained, deploy your chatbot using platforms like Gradio or Hugging Face Spaces for a simple, interactive frontend. The result is a fully functional AI chatbot that can answer questions and engage in conversations based on your original content—perfect for educators, creators, or businesses looking to automate knowledge-sharing.