In this short post, I will share a very brief GAN (Generative Adversarial Network) model and in practice, how do we train it using PyTorch. Also, I will include some tips about training as I myself found it is hard to train, especially when working with my own data and model. Training GAN models IContinue reading “Deep Learning 18: GANs with PyTorch”
Why BERT If you are a big fun of PyTorch and NLP, you must try to use the PyTorch based BERT implementation! If you have your own dataset and want to try the state-of-the-art model, BERT is a good choice. Please check the code from https://github.com/huggingface/pytorch-pretrained-BERT to get a close look. However, in this post,Continue reading “Deep Learning 17: text classification with BERT using PyTorch”
Why Graphs? Graph Convolution Networks (GCNs)  deal with graphs where the data form with a graph structure. A typical graph is represented as G(V, E), where V is the collection of all the nodes and Eis the collection of all the edges.
ELMo: Deep contextualized word representations In this blog, I show a demo of how to use pre-trained ELMo embeddings, and how to train your own embeddings.