allow customized head_dim

This is for resolving the ask in this [post](https://fb.workplace.com/groups/pytorch.edge.users/permalink/1574875706716050/).

Similar change in HF: huggingface/transformers#32502

Differential Revision: [D65974454](https://our.internmc.facebook.com/intern/diff/D65974454/)

[ghstack-poisoned]

examples/models/llama/llama_transformer.py

@@ -85,6 +85,7 @@ class ModelArgs:
     n_kv_heads: Optional[int] = None
     vocab_size: int = -1  # defined later by tokenizer
     hidden_dim: Optional[int] = None
+    head_dim: Optional[int] = None
     multiple_of: int = 256  # make SwiGLU hidden layer size multiple of large power of 2
     ffn_dim_multiplier: Optional[float] = None
     norm_eps: float = 1e-5
@@ -272,7 +273,7 @@ def __init__(self, args: ModelArgs, layer_id: int):
         self.n_local_heads = self.n_heads // model_parallel_size
         self.n_local_kv_heads = self.n_kv_heads // model_parallel_size
         self.n_rep = self.n_local_heads // self.n_local_kv_heads
-        self.head_dim = args.dim // self.n_heads
+        self.head_dim = args.dim // self.n_heads if args.head_dim is None else args.head_dim
         self.max_batch_size = args.max_batch_size
         self.max_seq_len = args.max_seq_len
         self.dim = args.dim