Review: Fine-tuned language models are zero-shot learners
In this article, we review several notable fine-tuned language models for their capabilities as zero-shot learners on diverse tasks.
In this article, we review several notable fine-tuned language models for their capabilities as zero-shot learners on diverse tasks.
In this deep dive, we show how to work with, pretrain, and finetune MosaicML models on Paperspace 8xH100 Machines.
In this tutorial we introduce and cover First-Order Model Agnostic Meta-Learning (MAML), which give fast understanding on new tasks to deep neural networks.
In this tutorial, we show how to get started with LangChain: a useful package for streamlining your Large Language Model pipelines.
in this tutorial, we look at how Transformers enables several classical NLP techniques like translation, classification, and segmentation of text.
In this tutorial, we discuss and show how to run MemGPT - an LLM with the potential for infinite context understanding.
In this tutorial, we look at HierSpeech++ - one of the newest and greatest speech synthesis models - on Papersapce.
Part 3 of our tutorial series on Meta Learning for NLP tasks.
In part 2 of this tutorial series on meta learning for NLP, we discuss different useful techniques for task construction.