minor fixes: Llama 3.2 standalone (#420)

* minor fixes

* reformat rope base as float

---------

Co-authored-by: rasbt <[email protected]>

Author: d-kleine

ch05/07_gpt_to_llama/converting-llama2-to-llama3.ipynb

@@ -907,7 +907,7 @@
     "    \"n_layers\": 32,          # Number of layers\n",
     "    \"hidden_dim\": 14_336,    # NEW: Larger size of the intermediate dimension in FeedForward\n",
     "    \"n_kv_groups\": 8,        # NEW: Key-Value groups for grouped-query attention\n",
-    "    \"rope_base\": 500_000,    # NEW: The base in RoPE's \"theta\" was increased to 500_000\n",
+    "    \"rope_base\": 500_000.0,  # NEW: The base in RoPE's \"theta\" was increased to 500_000\n",
     "    \"rope_freq\": None,       # NEW: Additional configuration for adjusting the RoPE frequencies\n",
     "    \"dtype\": torch.bfloat16  # Lower-precision dtype to save memory\n",
     "}"
@@ -2060,7 +2060,7 @@
     "    \"n_layers\": 32,          # Number of layers\n",
     "    \"hidden_dim\": 14_336,    # Size of the intermediate dimension in FeedForward\n",
     "    \"n_kv_groups\": 8,        # Key-Value groups for grouped-query attention\n",
-    "    \"rope_base\": 500_000,    # The base in RoPE's \"theta\"\n",
+    "    \"rope_base\": 500_000.0,  # The base in RoPE's \"theta\"\n",
     "    \"rope_freq\": None,       # Additional configuration for adjusting the RoPE frequencies\n",
     "    \"dtype\": torch.bfloat16  # Lower-precision dtype to save memory\n",
     "}\n",
@@ -2073,7 +2073,7 @@
     "    \"n_layers\": 32,             # Number of layers\n",
     "    \"hidden_dim\": 14_336,       # Size of the intermediate dimension in FeedForward\n",
     "    \"n_kv_groups\": 8,           # Key-Value groups for grouped-query attention\n",
-    "    \"rope_base\": 500_000,       # The base in RoPE's \"theta\"\n",
+    "    \"rope_base\": 500_000.0,     # The base in RoPE's \"theta\"\n",
     "    \"dtype\": torch.bfloat16,    # Lower-precision dtype to save memory\n",
     "    \"rope_freq\": {              # NEW: RoPE frequency scaling\n",
     "        \"factor\": 8.0,\n",
@@ -2447,7 +2447,7 @@
     "    \"n_layers\": 32,             # Number of layers\n",
     "    \"hidden_dim\": 14_336,       # Size of the intermediate dimension in FeedForward\n",
     "    \"n_kv_groups\": 8,           # Key-Value groups for grouped-query attention\n",
-    "    \"rope_base\": 500_000,       # The base in RoPE's \"theta\"\n",
+    "    \"rope_base\": 500_000.0,     # The base in RoPE's \"theta\"\n",
     "    \"dtype\": torch.bfloat16,    # Lower-precision dtype to save memory\n",
     "    \"rope_freq\": {              # NEW: RoPE frequency scaling\n",
     "        \"factor\": 8.0,\n",
@@ -2466,7 +2466,7 @@
     "    \"n_layers\": 16,             # NEW: Half the number of layers\n",
     "    \"hidden_dim\": 8192,         # NEW: Almost half the size of the intermediate dimension in FeedForward\n",
     "    \"n_kv_groups\": 8,           # Key-Value groups for grouped-query attention\n",
-    "    \"rope_base\": 500_000,       # The base in RoPE's \"theta\"\n",
+    "    \"rope_base\": 500_000.0,     # The base in RoPE's \"theta\"\n",
     "    \"dtype\": torch.bfloat16,    # Lower-precision dtype to save memory\n",
     "    \"rope_freq\": {              # RoPE frequency scaling\n",
     "        \"factor\": 32.0,         # NEW: Adjustment of the rescaling factor\n",

ch05/07_gpt_to_llama/standalone-llama32.ipynb

@@ -437,7 +437,7 @@
     "    \"n_layers\": 16,             # Number of layers\n",
     "    \"hidden_dim\": 8192,         # Size of the intermediate dimension in FeedForward\n",
     "    \"n_kv_groups\": 8,           # Key-Value groups for grouped-query attention\n",
-    "    \"rope_base\": 500_000,       # The base in RoPE's \"theta\"\n",
+    "    \"rope_base\": 500_000.0,     # The base in RoPE's \"theta\"\n",
     "    \"dtype\": torch.bfloat16,    # Lower-precision dtype to save memory\n",
     "    \"rope_freq\": {              # RoPE frequency scaling\n",
     "        \"factor\": 32.0,\n",
@@ -451,13 +451,13 @@
     "\n",
     "# LLAMA32_CONFIG = {\n",
     "#     \"vocab_size\": 128_256,      # Vocabulary size\n",
-    "#     \"context_length\": 131_000,  # Context length\n",
+    "#     \"context_length\": 131_072,  # Context length\n",
     "#     \"emb_dim\": 3072,            # Embedding dimension\n",
     "#     \"n_heads\": 24,              # Number of attention heads\n",
     "#     \"n_layers\": 28,             # Number of layers\n",
     "#     \"hidden_dim\": 8192,         # Size of the intermediate dimension in FeedForward\n",
     "#     \"n_kv_groups\": 8,           # Key-Value groups for grouped-query attention\n",
-    "#     \"rope_base\": 500_000,        # The base in RoPE's \"theta\"\n",
+    "#     \"rope_base\": 500_000.0,     # The base in RoPE's \"theta\"\n",
     "#     \"dtype\": torch.bfloat16,    # Lower-precision dtype to save memory\n",
     "#     \"rope_freq\": {              # RoPE frequency scaling\n",
     "#         \"factor\": 32.0,\n",
@@ -697,7 +697,6 @@
     "    def __init__(self, model_path):\n",
     "        assert os.path.isfile(model_path), f\"Model file {model_path} not found\"\n",
     "        mergeable_ranks = load_tiktoken_bpe(model_path)\n",
-    "        num_base_tokens = len(mergeable_ranks)\n",
     "\n",
     "        self.special_tokens = {\n",
     "            \"<|begin_of_text|>\": 128000,\n",
@@ -1013,7 +1012,8 @@
     "\n",
     "\n",
     "load_weights_into_llama(model, LLAMA32_CONFIG, combined_weights)\n",
-    "model.to(device);"
+    "model.to(device)\n",
+    "del combined_weights  # free up memory"
    ]
   },
   {