pyvene.models.llama.modelings_intervenable_llama.llama_type_to_dimension_mapping

llama_type_to_dimension_mapping = {'attention_input': ('hidden_size',), 'attention_output': ('hidden_size',), 'attention_value_output': ('hidden_size',), 'block_input': ('hidden_size',), 'block_output': ('hidden_size',), 'head_attention_value_output': ('hidden_size/num_attention_heads',), 'head_key_output': ('hidden_size/num_attention_heads',), 'head_query_output': ('hidden_size/num_attention_heads',), 'head_value_output': ('hidden_size/num_attention_heads',), 'key_output': ('hidden_size',), 'mlp_activation': ('intermediate_size',), 'mlp_input': ('hidden_size',), 'mlp_output': ('hidden_size',), 'n_head': ('num_attention_heads',), 'n_kv_head': ('num_key_value_heads',), 'query_output': ('hidden_size',), 'value_output': ('hidden_size',)}

llama model with LM head