Large Language Models (LLMs) are known to have “hallucinations.” This is a behavior in that the model speaks false knowledge as if it is accurate. In this post, you will learn why hallucinations are a nature of an LLM. Specifically, you will learn: Why LLMs hallucinate How to make hallucinations work for you How to […]
Search results for "language models"
What are Large Language Models
Large language models (LLMs) are recent advances in deep learning models to work on human languages. Some great use case of LLMs has been demonstrated. A large language model is a trained deep-learning model that understands and generates text in a human-like fashion. Behind the scene, it is a large transformer model that does all […]
How to Develop Word-Based Neural Language Models in Python with Keras
Language modeling involves predicting the next word in a sequence given the sequence of words already present. A language model is a key element in many natural language processing models such as machine translation and speech recognition. The choice of how the language model is framed must match how the language model is intended to […]
Gentle Introduction to Statistical Language Modeling and Neural Language Models
Language modeling is central to many important natural language processing tasks. Recently, neural-network-based language models have demonstrated better performance than classical methods both standalone and as part of more challenging natural language processing tasks. In this post, you will discover language modeling for natural language processing. After reading this post, you will know: Why language […]
Primer on Neural Network Models for Natural Language Processing
Deep learning is having a large impact on the field of natural language processing. But, as a beginner, where do you start? Both deep learning and natural language processing are huge fields. What are the salient aspects of each field to focus on and which areas of NLP is deep learning having the most impact? […]
Brief Introduction to Diffusion Models for Image Generation
The advance of generative machine learning models makes computers capable of creative work. In the scope of drawing pictures, there are a few notable models that allow you to convert a textual description into an array of pixels. The most powerful models today are part of the family of diffusion models. In this post, you […]
PyTorch Tutorial: How to Develop Deep Learning Models with Python
Predictive modeling with deep learning is a skill that modern developers need to know. PyTorch is the premier open-source deep learning framework developed and maintained by Facebook. At its core, PyTorch is a mathematical library that allows you to perform efficient computation and automatic differentiation on graph-based models. Achieving this directly is challenging, although thankfully, […]
Save and Load Your PyTorch Models
A deep learning model is a mathematical abstraction of data, in which a lot of parameters are involved. Training these parameters can take hours, days, and even weeks but afterward, you can make use of the result to apply on new data. This is called inference in machine learning. It is important to know how […]
Use PyTorch Deep Learning Models with scikit-learn
The most popular deep learning libraries in Python for research and development are TensorFlow/Keras and PyTorch, due to their simplicity. The scikit-learn library, however, is the most popular library for general machine learning in Python. In this post, you will discover how to use deep learning models from PyTorch with the scikit-learn library in Python. […]
Building Transformer Models with Attention Crash Course. Build a Neural Machine Translator in 12 Days
Transformer is a recent breakthrough in neural machine translation. Natural languages are complicated. A word in one language can be translated into multiple words in another, depending on the context. But what exactly a context is, and how you can teach the computer to understand the context was a big problem to solve. The invention […]