Covering latest technical advancements in LLMs, CV and NLP
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Retrieving documents from external sources gives language models access to data that they didn’t see during training. Particularly for question-answering systems where you want the model to answer questions based on specific documents and n...
The most common evaluating metrics for large language models are:
In 2017, Ashish Vaswani et al wrote a paper that would change the natural language processing (NLP) scene forever, and most recently even computer vision. The authors proposed an efficient way to solve NLP problems without using Recurrent o...
Until recently, fine-tuning large language models (LLMs) on a single GPU was a pipe dream. This is because of the large size of these models, leading to colossal memory and storage requirements. For example, you need 780 GB of GPU memory to...
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