# 3. Transformers Transformers\ These models, introduced in the paper "Attention is All You Need", use self-attention mechanisms and are very effective for many NLP tasks. Variants include: (a) Transformer (base model) (b) BERT (Bidirectional Encoder Representations from Transformers) (c) GPT (Generative Pretrained Transformer) (d) T5 (Text-to-Text Transfer Transformer) (e) BART (Bidirectional and Auto-Regressive Transformers) (f) RoBERTa, ALBERT, DistilBERT (variants of BERT with different training strategies or model sizes) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://metaverse-imagen.gitbook.io/ai-tools-research/ai-technology/ann-deep-learning-architectures/3.-transformers.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.