Calculating parameters and what does that mean - straight from Chat GPT
This is a question from Chat GPT and Sebastain's book on large language models from scratch. First, this data is interesting. 124 Million parameters GPT_CONFIG_124M = { "vocab_size": 50257, # Vocabulary size "context_length": 1024, # Context length "emb_dim": 768, # Embedding dimension "n_heads": 12, # Number of attention heads "n_layers": 12, # Number of layers "drop_rate": 0.1, # Dropout rate "qkv_bias": False # Query-Key-Value bias } The 1.5 billion parameter GPT model config GPT_CONFIG_1558M = { "vocab_size": 50257, # Vocabulary size "context_length": 1024, # Context length "emb_dim": 1600, # ...