Mastering Large Language Models : Key Insights, Applications, Advantages and Challenges !!
Abstract: Large language models (LLMs) are AI models that can perform a variety of natural language processing tasks. Some examples of LLMs include: T5 Developed by Google, this model has 11 billion parameters and can perform tasks like text classification, translation, and text generation. Falcon An open-source LLM developed by TII, this model is known for its accuracy, versatility, and faster training. GPT-4 An example of a multimodal LLM, which can accept other types of data inputs like images. Here are some other things to know about LLMs: Training: LLMs can take months to train and consume a lot of resources. Bias: LLMs are trained on human language, so they can introduce bias in race, gender, religion, and more. Fine-tuning: LLMs can be fine-tuned by training them on a new corpus of text. Edge models: These models are small in size and can be fine-tuned or trained from scratch on small data sets. LLMOps: This stands for Large Language Model