Last updated: 19th April, 2024 Model parallelism and data parallelism are two strategies used to distribute the training of large…
In the dynamic realm of AI, where labeled data is often scarce and costly, self-supervised learning helps unlock new machine…
Last updated: 31st Jan, 2024 Large language models (LLMs), being the key pillar of generative AI, have been gaining traction in…
Last updated: 23rd Jan, 2024 Two NLP concepts that are fundamental to large language models (LLMs) are transfer learning and…
The Transformer model architecture, introduced by Vaswani et al. in 2017, is a deep learning model that has revolutionized the…
A pre-trained or foundation model is further trained (or fine-tuned) with instructions datasets to help them learn about your specific…
Training large language models (LLMs) like GPT-4 requires the use of distributed computing patterns as there is a need to…
Are you fascinated by the power of deep learning large language models that can generate creative writing, answer complex questions,…
NLP has been around for decades, but it has recently seen an explosion in popularity due to pre-trained models (PTMs),…
Have you been wondering what sets apart two of the most prominent transformer-based machine learning models in the field of…