As data scientists and MLOps Engineers, you must have come across the challenges related to managing GPU requirements for training…
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…
NLP has been around for decades, but it has recently seen an explosion in popularity due to pre-trained models (PTMs),…
At the heart of NLP lies a fundamental element: the corpus. A corpus, in NLP, is not just a collection…
In the field of AI / machine learning, the encoder-decoder architecture is a widely-used framework for developing neural networks that…
The attention mechanism workflow in the context of transformers in NLP, is a process that enables the model to dynamically…
Have you ever wondered how your smartphone seems to know exactly what you're going to type next? Or how virtual…
Last updated: 6th Jan, 2024 Most machine learning algorithms require numerical input for training the models. Bag of words (BoW)…
Last updated: 5th Jan, 2024 Have you ever wondered how your phone's voice assistant understands your commands and responds appropriately?…