NLP
Small Language Models
·1096 words·6 mins
Small Language Models (SLMs) are a specialized type of artificial intelligence designed for natural language processing (NLP) tasks. Unlike Large Language Models (LLMs), which are characterized by their vast size and extensive training datasets, SLMs are built to be more efficient and effective for specific applications.
From CNNs to Vision Transformers: The Future of Image Recognition
·6015 words·29 mins
Vision Transformers (ViTs) are redefining image recognition by using Transformer models to capture global context, unlike traditional Convolutional Neural Networks (CNNs) that focus on local features. ViTs excel with large datasets and show impressive scalability and performance.
Transformers & Attention
·866 words·5 mins
This blog post explains how self-attention and softmax function in Transformer models, crucial for modern NLP. It breaks down how self-attention helps models understand relationships between tokens and how softmax ensures efficient computation and numerical stability.
Less is More Paper Review
·467 words·3 mins
Less is More: Parameter-Free Text Classification with Gzip offers a novel text classification method using gzip compression, eliminating manual parameter tuning.