In part 2 of this tutorial series on meta learning for NLP, we discuss different useful techniques for task construction.
in this article, we overview several notable techniques for facilitating text classification with deep learning.
Introducing Falcon, an advanced language model designed for intricate natural language processing tasks. In this tutorial we will gain an in depth knowledge on Falcon model and also use Paperspace GPUs to load and run the model.
In this article, we introduce the Transformers package, and detail how it facilitates notable NLP models like RoBERTa, SATformer, GPT-f, and more.
In this article, we break down the paper "Towards Reasoning in Large Language Models: A Survey" in an attempt to explain relevant reasoning concepts used by LLMs.
In this tutorial we show how to implement iNLG with Python code in a Gradient Notebook.
In part 1 of this series on meta learning for Natural Language Processing, we introduce optimization and loss functions in machine learning used to approach meta learning with enhanced learning algorithms.
In this tutorial, we overview and explain the basics of working with the T5 model.
In this tutorial, we show how to fine-tune the powerful LLaMA 2 model with Paperspace's Nvidia Ampere GPUs.
