000			01503nam a22001697a 4500
008			240203b |||||||| |||| 00| 0 eng d
020			_a9781803247335
040			_cZET-ke
050			_aQA76.9 .N38 _b .R68 2022
100			_aRothman Denis.
245			_aTransformers for natural language processing: _bBuild train and finetune deep neural network architectures for NLP with python hugging face and open AIs GPT-3 ChatGP and GPT-4. _cDennis Rothmsn.
250			_a2rd ed.
260			_aBirmingham: _bPackt; _cc2022.
300			_axxxiii, 565p.: _bill.; _c24cm.
505			_aWhat are Transformers -- Getting Started with the Architecture of the Transformer Model -- Fine-Tuning BERT Models -- Pretraining a RoBERTa Model from Scratch -- Downstream NLP Tasks with Transformers -- Machine Translation with the Transformer -- The Rise of Suprahuman Transformers with GPT-3 Engines -- Applying Transformers to Legal and Financial Documents for AI Text Summarization -- Matching Tokenizers and Datasets -- Semantic Role Labeling with BERT-Based Transformers -- Let Your Data Do the Talking: Story, Questions, and Answers -- Detecting Customer Emotions to Make Predictions -- Analyzing Fake News with Transformers -- Interpreting Black Box Transformer Models -- From NLP to Task-Agnostic Transformer Models -- The Emergence of Transformer-Driven Copilots -- The Consolidation of Suprahuman Transformers with OpenAI’s ChatGPT and GPT-4.
942			_2lcc _cBK _hQA76.9 .N38 _kQA76.9 .N38 _m .R68 2022
999			_c5919 _d5919