Transformers interview questions.
A curated set of 21 questions that repeatedly exercise Transformers concepts in AI/ML interviews.
How is BERT different from GPT?GenAI & LLM · medium · Evidence 88/100Explain Transformer architecture and each major component.GenAI & LLM · medium · Evidence 88/100Explain the attention mechanism in a Transformer.GenAI & LLM · medium · Evidence 78/100Implement self-attention.ML Coding & PyTorch · hard · Evidence 77/100How does an LSTM differ from a Transformer?GenAI & LLM · medium · Evidence 75/100Explain Transformer fundamentals for a multimodal role.GenAI & LLM · medium · Evidence 75/100Explain attention in modern neural networks.GenAI & LLM · medium · Evidence 75/100What are sparse-attention methods in Transformers?GenAI & LLM · hard · Evidence 75/100Describe the Segment Anything Model (SAM) and how it worksML Fundamentals · medium · Evidence 75/100Implement self-attention from scratch in code.ML Coding & PyTorch · hard · Evidence 75/100Explain Transformers in an NLP context.GenAI & LLM · medium · Evidence 75/100How can Transformers be used in recommendation systems?GenAI & LLM · hard · Evidence 75/100Analyze the space complexity of major Transformer components.GenAI & LLM · hard · Evidence 75/100Explain the architecture of attention.GenAI & LLM · medium · Evidence 75/100Explain the relationship between self-attention and Transformer representations.GenAI & LLM · medium · Evidence 41/100BERT: Architecture and TrainingML Fundamentals · medium · Evidence 41/100When would you choose a CNN over a Vision Transformer?ML Fundamentals · medium · Evidence 41/100Estimate Transformer FLOPsML Math · hard · Evidence 34/100Transformer vs RNNGenAI & LLM · medium · Evidence 34/100Implement a Transformer BlockML Coding & PyTorch · hard · Evidence 34/100Implement a Transformer encoder layerML Coding & PyTorch · medium · Evidence 31/100