Generative pre-trained transformer

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Related lectures (31)

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Explores pretraining models like BERT, T5, and GPT, discussing their training objectives and applications in natural language processing.

Custom GPTs for Academic Writing

Delves into the use of custom GPTs for academic writing, highlighting the balance between AI assistance and traditional learning methods.

Transformers: Pre-Training

Discusses challenges and advancements in Transformers, pretraining models, and subword tokenization in NLP.

Transformers: Pretraining and Decoding Techniques

Covers advanced transformer concepts, focusing on pretraining and decoding techniques in NLP.

Generative Models: Self-Attention and Transformers

Covers generative models with a focus on self-attention and transformers, discussing sampling methods and empirical means.

Pretraining Sequence-to-Sequence Models: BART and T5

Covers the pretraining of sequence-to-sequence models, focusing on BART and T5 architectures.

Pre-Training: BiLSTM and Transformer

Delves into pre-training BiLSTM and Transformer models for NLP tasks, showcasing their effectiveness and applications.

Contextual Representations: ELMo & BERT

Explores the development of contextualized embeddings in NLP, focusing on ELMo and BERT's advancements and impact on NLP tasks.

Coreference Resolution: Models and Evaluation

Explores coreference resolution models, challenges in scoring spans, graph refinement techniques, state-of-the-art results, and the impact of pretrained Transformers.

Contextual Representations: ELMO and BERT Overview

Covers contextual representations in NLP, focusing on ELMO and BERT architectures and their applications in various tasks.