Writing an LLM from scratch, part 17 – the feed-forward network
11 days ago
- #LLM
- #neural-networks
- #machine-learning
- The feed-forward network in LLMs is crucial for processing context vectors after attention mechanisms.
- It consists of two linear layers with a GELU activation function, expanding and then reducing dimensions.
- Attention mechanisms gather information, but feed-forward networks perform the 'thinking' or pattern-matching.
- Feed-forward networks contain more parameters than attention mechanisms, indicating their importance.
- A single hidden layer in the feed-forward network acts as a universal approximator.
- The author initially underestimated the role of feed-forward networks in LLMs.
- Future posts may explore deeper networks and related research papers.