@techNmak: These are literally the kind of LLM interview questions most candidates wish they had seen earlier. A curated list of 5…

These are literally the kind of LLM interview questions most candidates wish they had seen earlier. A curated list of 50 LLM interview questions - shared by Hao Hoang. What's covered: Fundamentals: → Tokenization and why it matters → Attention mechanisms in transformers → Context windows and their tradeoffs → Embeddings and initialization → Positional encodings Fine-tuning & Efficiency: → LoRA vs QLoRA → PEFT to prevent catastrophic forgetting → Model distillation → Adaptive Softmax for large vocabularies Generation & Decoding: → Beam search vs greedy decoding → Temperature, top-k, top-p sampling → Autoregressive vs masked models Advanced Concepts: → RAG (Retrieval-Augmented Generation) → Chain-of-Thought prompting → Mixture of Experts (MoE) → Knowledge graph integration → Zero-shot and few-shot learning Math & Theory: → Softmax in attention → Cross-entropy loss → KL divergence → Gradient computation for embeddings → Vanishing gradient solutions in transformers You don't need to follow me (@techNmak) and comment "LLM". I will put the link in the comments.