Educational
Understanding the Quants of Qwen1.5 110B Chat

Understanding the Quants of Qwen1.5 110B Chat

With the release of Qwen1.5 110B Chat, the AI community has taken note of the advancements in quantization, specifically regarding how much information can be stored in a model's weights. In this article, we'll delve into the intricacies of quants, their implications,...

How to Generate Instructions with T5 and PyTorch

How to Generate Instructions with T5 and PyTorch

In this blog post, we will explore how to use the T5 model from Hugging Face Transformers to generate paraphrased instructions dynamically. This powerful technique can be handy in situations like responding to user queries in applications. Let’s dive into the code and...

How to Configure Your Neural Network: A Step-by-Step Guide

How to Configure Your Neural Network: A Step-by-Step Guide

In the ever-evolving world of artificial intelligence, fine-tuning your neural network is akin to adjusting the dials on a sophisticated machine. Each parameter plays a crucial role in ensuring that your model learns accurately. In this article, we will delve into how...

How to Fine-Tune the CoMet-based OCR System using TROCR

How to Fine-Tune the CoMet-based OCR System using TROCR

Are you ready to step into the world of Optical Character Recognition (OCR) with the power of TROCR (Transformer OCR)? In this guide, we will walk you through the process of setting up and fine-tuning a specificity-driven OCR model using the beit+roberta architecture....