It’s Day 8 of Building LLMs from Scratch: Implemented self-attention, the core mechanism behind transformers and GPT models! This involves computing attention scores using scaled dot-product attention: 1. Project inputs into Query (Q), Key (K), and Value (V) matrices 2. Compute attention scores using Q · Kᵀ / sqrt(d_k) 3. Apply softmax to get attention weights 4. Multiply with V to get the weighted output This lets the model focus on relevant parts of the input—like how each word relates to others in a sentence!#deeplearning #generativeai #30dayschallenge #womenwhocode #datascience #largelanguagemodels #womenintech