GitHub - zihangdai/xlnet: XLNet: Generalized Autoregressive Pretraining for Language Understanding

🚀 Dive into the world of advanced language understanding with XLNet! 📚⚙️ ✨ XLNet is an unsupervised language representation learning tool that outshines the competition with its Transformer-XL backbone. 🔍📈 Achieve state-of-the-art results in question answering, sentiment analysis, & more! 🔗 Learn more: github.com/zihangdai/xlnet #AI #NLP #XLNet #LanguageUnderstanding

XLNet is an unsupervised language representation learning method based on a generalized permutation language modeling objective.
It employs Transformer-XL as the backbone model and excels in tasks requiring long context understanding.
XLNet achieves state-of-the-art results across various language tasks including question answering, sentiment analysis, and document ranking.
XLNet outperforms BERT on numerous tasks and has shown strong results in tasks like reading comprehension and text classification.
XLNet offers pre-trained models such as XLNet-Large and XLNet-Base for different configurations.
The models are available in cased versions and come with TensorFlow checkpoints, a Sentence Piece model, and a config file.
Future releases include more pretrained models with different settings for tasks like Wikipedia text tasks and specific downstream tasks.
XLNet faces memory issues during finetuning, mainly due to large data sizes, but workarounds like gradient accumulation are being explored.
Options for finetuning with XLNet are provided, along with examples for different settings like using GPUs or TPUs.
The repository includes scripts for tasks like text classification/regression, SQuAD dataset, and RACE reading comprehension.
Pretraining XLNet involves steps like preprocessing text data into tfrecords and adjusting hyperparameters for the model.
XLNet is a powerful tool for language understanding, offering flexibility for various NLP tasks.