Digests » 111

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TextAttack 🐙 Generating adversarial examples for NLP models

TextAttack is a Python framework for adversarial attacks, data augmentation, and model training in NLP.

BERTology Meets Biology: Interpreting Attention in Protein Language Models

Proteins are the workhorses of almost all cellular functions and a core component of life. But despite their versatility, all proteins are built as sequences of the same 20 amino acids. These sequences can be analyzed with tools from NLP. This paper investigates the attention mechanism of a BERT model that has been trained on protein sequence data and discovers that the language model has implicitly learned non-trivial higher-order biological properties of proteins.

PyTorch LSTM: Text Generation Tutorial

Long Short Term Memory (LSTM) is a popular Recurrent Neural Network (RNN) architecture. This tutorial covers using LSTMs on PyTorch for generating text; in this case - pretty lame jokes.

Hugging Captions: Generate realistic Instagram captions

Hugging Captions fine-tunes GPT-2, a transformer-based language model by OpenAI, to generate realistic photo captions. All of the transformer stuff is implemented using Hugging Face's Transformers library, hence the name Hugging Captions.

Google Colab Tips for Power Users

Colab is one of the best products to come from Google. It has made GPUs freely accessible to learners and practitioners like me who otherwise wouldn’t be able to afford a high-end GPU.