Words to vector, catch word meanings by word embeddings. Representing words One-Hot Encoding Choose a vocabulary, each word in your sample is represented by a one-hot vector (shape
Category
NLP
5 articles in this topic.
-
-
Notes for NLP project Questions and Solutions 1. Llama2 Model takes more than 40G GPU RAM to train. Solution: LoRA: Low-Rank Adaptation of Large Language Models Concepts: Instead o
-
Record problems in the "BERT" paper. Process Analysis 1. masked language model: randomly mask some of the input tokens, and predict the originally vocab id of the mask ones. 2. nex
-
Recording a task to solve a movie comment sentiment analysis task Data Preprocessing Dataset downloading Download movie comments dataset (IMDb) from Hugging Face Data Cleaning Part
-
Sequence Models and RNN Why use sequence models? Sequence models are used to situations when you have sequential input (e.g. images fo a human action, a paragraph of text or empty)
