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Tag: Decoder-only transformer
The Saga of Recurrent Sequential Models, RNNs vs Transformers: The Final Showdown?
In the context of machine learning, a showdown has emerged between two architectural giants—Recurrent Sequential Models and Transformers. These approaches represent two fundamentally different philosophies for processing sequential data, with each excelling in different aspects of learning from sequences. On one side, Recurrent Sequential Models (RNNs, LSTMs, GRUs) have long been the go-to for tasks…
How to Get Started with Decoder-Only Transformers
Get started with decoder-only transformers, like OpenAI’s GPT models! Decoder-only transformers have gained massive popularity due to their success in tasks like text generation, summarization, dialogue systems, and code generation. These models utilize only the decoder portion of the original transformer architecture, focusing on generating sequences autoregressively—meaning they predict the next token in a sequence…
Exploring Decoder-Only Transformers for NLP and More
Learn about decoder-only transformers, a streamlined neural network architecture for natural language processing (NLP), text generation, and more. Discover how they differ from encoder-decoder models in this detailed guide.