Welcome to the "Text Generation with PyTorch" repository! This repository is dedicated to showcasing various techniques and examples of text generation using PyTorch.
The bigram model is used to generate characters. We train the model using a notebook written by a wizard as the dataset, which consists of 81 unique characters. Each character is represented as a (1 * 1) vector. Since there are 81 characters and each batch has 4 blocks, with each block containing 8 characters, the input dimension for the model is (4 * 8 * 81) after applying the nn.Embedding. After reshaping the tensor, the dimension becomes (32 * 81). In other words, the reshaped vector represents 32 characters, and we use it to predict the next most probable character.