<ul><li>Part 1 provides an overview of LLMs, discussing their advantages, disadvantages, and use cases.</li><li>Some important LLM models/frameworks/tools with pros, cons, and use cases are listed below. The ones given are GPT-3.5, GPT-4, GPT-2, LLaMA 2, Alpaca, DistilBERT, MiniLM, TinyBERT, BERT, Sentence-BERT, RoBERTa, Faiss (Facebook AI Similarity Search), ONNX Runtime, TensorRT, Hugging Face Transformers, Transformers.js, and ggml.</li><li>Type: Large Transformer-based LLM</li><li>Type: Medium-sized LLM</li><li>Type: LLM</li><li>Type: Fine-tuned LLaMA</li><li>Type: Transformer-based LLM</li><li>Type: Transformer-based LLM</li><li>Type: Transformer-based LLM</li><li>Type: Sentence Embedding Model</li></ul>

Scaling Smarter: An Overview of Large Language Models (LLMs) and Their Compression Techniques Part…

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