Parameter-efficient Fine-tuning (PEFT) is a technique used in Natural Language Processing (NLP) to improve the performance of pre-trained language models on specific downstream tasks.
Language models are the backbone of natural language processing (NLP) and have changed how we interact with language and technology.
Auto-GPT is an autonomous tool that allows large language models (LLMs) to operate autonomously, enabling them to think, plan and execute actions without constant human intervention.
EDA allows for exploring and examining data for important insights before the actual data analysis process begins. Check out this article to explore the importance, process and techniques of EDA.
By understanding the architecture of generative AI, enterprises can make informed decisions about which models and techniques to use for different use cases.
Reinforcement learning from human feedback (RLHF) is a machine learning approach that leverages a combination of human feedback and reinforcement learning to train AI models.
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