Enlace del recurso

Enlace del recurso

Enlace del recurso

Acceso restringido con credenciales UPSA

Enlace del recurso

Tabla de Contenidos: “…-- The rise of Transformer 4.0 seamless APIs -- Choosing ready-to-use API-driven libraries -- Choosing a Transformer Model -- The role of Industry 4.0 artificial intelligence specialists -- Summary -- Questions -- References -- Chapter 2: Getting Started with the Architecture of the Transformer Model -- The rise of the Transformer: Attention is All You Need -- The encoder stack -- Input embedding -- Positional encoding -- Sublayer 1: Multi-head attention -- Sublayer 2: Feedforward network -- The decoder stack -- Output embedding and position encoding -- The attention layers -- The FFN sublayer, the post-LN, and the linear layer -- Training and performance -- Tranformer models in Hugging Face -- Summary -- Questions -- References -- Chapter 3: Fine-Tuning BERT Models -- The architecture of BERT -- The encoder stack -- Preparing the pretraining input environment -- Pretraining and fine-tuning a BERT model -- Fine-tuning BERT -- Hardware constraints -- Installing the Hugging Face PyTorch interface for BERT -- Importing the modules -- Specifying CUDA as the device for torch -- Loading the dataset -- Creating sentences, label lists, and adding BERT tokens -- Activating the BERT tokenizer -- Processing the data -- Creating attention masks -- Splitting the data into training and validation sets -- Converting all the data into torch tensors -- Selecting a batch size and creating an iterator -- BERT model configuration…”

“…Desde fines del siglo II hasta la Paz de Constantino…”

“…Tributación de las entidades sin fines de lucro…”