Part 1.2: Counting Parameters in Decoder-Only Transformers

1. 1Identify the architecture of your transformer model
2. 2Determine the number of layers and attention heads in the decoder
3. 3Calculate the number of parameters in each layer using the formula for decoder-only transformers
4. 4Sum up the parameters from all layers to get the total parameter count
5. 5Use the total parameter count to estimate FLOPs, memory, and distributed training requirements

ML engineers and researchers working with transformer models can benefit from this knowledge to optimize their models' performance and resource allocation

💡 Accurate parameter counting is essential for optimizing transformer models' performance and resource allocation

💡 Counting parameters in decoder-only transformers is crucial for estimating FLOPs, memory, and distributed training requirements