6 Topics
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## Introduction Text-to-speech (TTS) technology has revolutionized how we interact with devices, making accessing content through auditory means easier. TTS is vital in various applications such as virtual assistants, audiobooks, accessibility tools for the visually impaired, and language learning platforms. This tutorial will explore how to convert text-to-speech using Hugging … | |
In this tutorial, you will see how to generate stunning AI-generated images from text inputs using state-of-the-art diffusion models from [Hugging Face](https://huggingface.co/). You'll learn about base diffusion models and how combining them with a refiner creates even more detailed, refined results. Diffusion models are powerful because they iteratively refine an … | |
In a previous article, I explained [how to extract tabular data from PDF image documents using Multimodal Google Gemini Pro](https://www.daniweb.com/programming/computer-science/tutorials/541449/pdf-image-table-extractor-web-app-with-google-gemini-pro-and-streamlit#post2296083). However, there are a couple of disadvantages with Google Gemini Pro. First, Google Gemini Pro is not free, and second, it needs complex prompt engineering to retrieve table, columns, and … | |
In my [previous articles](https://www.daniweb.com/programming/computer-science/tutorials/541732/paris-olympics-ticket-information-chatbot-with-memory-using-langchain), I explained how to develop customized chatbots using Retrieval Augmented Generation (RAG) approach in [LangChain](https://www.langchain.com/). However, I used proprietary models such as OpenAI, which can be expensive when you try to scale. In this article, I will show you how to use the open-source and free-of-cost … | |
In a previous article, I explained [how to fine-tune Google's Gemma model for text classification](https://www.daniweb.com/programming/computer-science/tutorials/541544/fine-tuning-google-gemma-model-for-text-classification-in-python). In this article, I will explain how you can improve performance of a pretrained large language model (LLM) using retrieval augmented generation (RAG) technique. So, let's begin without ado. ## What is Retrieval Augmented Generation … | |
In this tutorial, you will learn to fine-tune a [Hugging Face Transformers model](https://huggingface.co/docs/transformers/index) for video classification in PyTorch. The Hugging Face documentation provides an example of performing video classification using the Hugging Face Trainer with one of Hugging Face's built-in datasets. However, the process of fine-tuning a video transformer on … |
The End.