diff --git a/.gitignore b/.gitignore
index 2656934..bd9c2f8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -31,6 +31,7 @@ appendix-E/01_main-chapter-code/gpt2
ch05/01_main-chapter-code/gpt2/
ch05/02_alternative_weight_loading/checkpoints
+ch05/02_alternative_weight_loading/*.safetensors
ch05/01_main-chapter-code/model.pth
ch05/01_main-chapter-code/model_and_optimizer.pth
ch05/03_bonus_pretraining_on_gutenberg/model_checkpoints
diff --git a/ch05/01_main-chapter-code/ch05.ipynb b/ch05/01_main-chapter-code/ch05.ipynb
index de627c3..b1f4ee2 100644
--- a/ch05/01_main-chapter-code/ch05.ipynb
+++ b/ch05/01_main-chapter-code/ch05.ipynb
@@ -2103,7 +2103,20 @@
"id": "127ddbdb-3878-4669-9a39-d231fbdfb834",
"metadata": {},
"source": [
- "- For an alternative way to load the weights from the Hugging Face Hub, see [../02_alternative_weight_loading](../02_alternative_weight_loading)"
+ "\n",
+ " \n",
+ " - For an alternative way to load the weights from the Hugging Face Hub, see ../02_alternative_weight_loading
\n",
+ " \n",
+ " - This is useful if:
\n",
+ " \n",
+ " - the weights are temporarily unavailable
\n",
+ " - a company VPN only permits downloads from the Hugging Face Hub but not from the OpenAI CDN, for example
\n",
+ " - you are having trouble with the TensorFlow installation (the original weights are stored in TensorFlow files)
\n",
+ "
\n",
+ "
\n",
+ " - The ../02_alternative_weight_loading code notebooks are replacements for the remainder of this section 5.5
\n",
+ "
\n",
+ "\n"
]
},
{
@@ -2505,7 +2518,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.6"
+ "version": "3.11.4"
}
},
"nbformat": 4,
diff --git a/ch05/01_main-chapter-code/gpt_generate.py b/ch05/01_main-chapter-code/gpt_generate.py
index 92c0010..4e49ccd 100644
--- a/ch05/01_main-chapter-code/gpt_generate.py
+++ b/ch05/01_main-chapter-code/gpt_generate.py
@@ -155,8 +155,8 @@ def assign(left, right):
def load_weights_into_gpt(gpt, params):
- gpt.pos_emb.weight = assign(gpt.pos_emb.weight, params['wpe'])
- gpt.tok_emb.weight = assign(gpt.tok_emb.weight, params['wte'])
+ gpt.pos_emb.weight = assign(gpt.pos_emb.weight, params["wpe"])
+ gpt.tok_emb.weight = assign(gpt.tok_emb.weight, params["wte"])
for b in range(len(params["blocks"])):
q_w, k_w, v_w = np.split(
@@ -229,7 +229,7 @@ def generate(model, idx, max_new_tokens, context_size, temperature=0.0, top_k=No
# Keep only top_k values
top_logits, _ = torch.topk(logits, top_k)
min_val = top_logits[:, -1]
- logits = torch.where(logits < min_val, torch.tensor(float('-inf')).to(logits.device), logits)
+ logits = torch.where(logits < min_val, torch.tensor(float("-inf")).to(logits.device), logits)
# New: Apply temperature scaling
if temperature > 0.0:
diff --git a/ch05/02_alternative_weight_loading/README.md b/ch05/02_alternative_weight_loading/README.md
index c2056e9..7eb4e7b 100644
--- a/ch05/02_alternative_weight_loading/README.md
+++ b/ch05/02_alternative_weight_loading/README.md
@@ -3,3 +3,5 @@
This folder contains alternative weight loading strategies in case the weights become unavailable from OpenAI.
- [weight-loading-hf-transformers.ipynb](weight-loading-hf-transformers.ipynb): contains code to load the weights from the Hugging Face Model Hub via the `transformers` library
+
+- [weight-loading-hf-safetensors.ipynb](weight-loading-hf-safetensors.ipynb): contains code to load the weights from the Hugging Face Model Hub via the `safetensors` library directly (skipping the instantiation of a Hugging Face transformer model)
\ No newline at end of file
diff --git a/ch05/02_alternative_weight_loading/weight-loading-hf-safetensors.ipynb b/ch05/02_alternative_weight_loading/weight-loading-hf-safetensors.ipynb
new file mode 100644
index 0000000..91a1020
--- /dev/null
+++ b/ch05/02_alternative_weight_loading/weight-loading-hf-safetensors.ipynb
@@ -0,0 +1,314 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "6d6bc54f-2b16-4b0f-be69-957eed5d112f",
+ "metadata": {},
+ "source": [
+ "
\n",
+ "\n",
+ "\n",
+ "\n",
+ "Supplementary code for the Build a Large Language Model From Scratch book by Sebastian Raschka \n",
+ " Code repository: https://github.com/rasbt/LLMs-from-scratch\n",
+ "\n",
+ " | \n",
+ "\n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "72953590-5363-4398-85ce-54bde07f3d8a",
+ "metadata": {},
+ "source": [
+ "# Bonus Code for Chapter 5"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1a4ab5ee-e7b9-45d3-a82b-a12bcfc0945a",
+ "metadata": {},
+ "source": [
+ "## Alternative Weight Loading from Hugging Face Model Hub Via `safetensors`"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b2feea87-49f0-48b9-b925-b8f0dda4096f",
+ "metadata": {},
+ "source": [
+ "- In the main chapter, we loaded the GPT model weights directly from OpenAI\n",
+ "- This notebook provides alternative weight loading code to load the model weights from the [Hugging Face Model Hub](https://huggingface.co/docs/hub/en/models-the-hub) using `.safetensors` files\n",
+ "- This is conceptually the same as loading weights of a PyTorch model from via the state-dict method described in chapter 5:\n",
+ "\n",
+ "```python\n",
+ "state_dict = torch.load(\"model_state_dict.pth\")\n",
+ "model.load_state_dict(state_dict) \n",
+ "```\n",
+ "\n",
+ "- The appeal of `.safetensors` files lies in their secure design, as they only store tensor data and avoid the execution of potentially malicious code during loading\n",
+ "- In newer versions of PyTorch (e.g., 2.0 and newer), a `weights_only=True` argument can be used with `torch.load` (e.g., `torch.load(\"model_state_dict.pth\", weights_only=True)`) to improve safety by skipping the execution of code and loading only the weights (this is now enabled by default in PyTorch 2.6 and newer)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "99b77109-5215-4d07-a618-4d10eff1a488",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# pip install safetensors"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "b0467eff-b43c-4a38-93e8-5ed87a5fc2b1",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "numpy version: 1.26.4\n",
+ "torch version: 2.5.1\n",
+ "safetensors version: 0.4.4\n"
+ ]
+ }
+ ],
+ "source": [
+ "from importlib.metadata import version\n",
+ "\n",
+ "pkgs = [\"numpy\", \"torch\", \"safetensors\"]\n",
+ "for p in pkgs:\n",
+ " print(f\"{p} version: {version(p)}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "d1cb0023-8a47-4b1a-9bde-54ab7eac476b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from previous_chapters import GPTModel, generate_text_simple"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "9ea9b1bc-7881-46ad-9555-27a9cf23faa7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "BASE_CONFIG = {\n",
+ " \"vocab_size\": 50257, # Vocabulary size\n",
+ " \"context_length\": 1024, # Context length\n",
+ " \"drop_rate\": 0.0, # Dropout rate\n",
+ " \"qkv_bias\": True # Query-key-value bias\n",
+ "}\n",
+ "\n",
+ "model_configs = {\n",
+ " \"gpt2-small (124M)\": {\"emb_dim\": 768, \"n_layers\": 12, \"n_heads\": 12},\n",
+ " \"gpt2-medium (355M)\": {\"emb_dim\": 1024, \"n_layers\": 24, \"n_heads\": 16},\n",
+ " \"gpt2-large (774M)\": {\"emb_dim\": 1280, \"n_layers\": 36, \"n_heads\": 20},\n",
+ " \"gpt2-xl (1558M)\": {\"emb_dim\": 1600, \"n_layers\": 48, \"n_heads\": 25},\n",
+ "}\n",
+ "\n",
+ "\n",
+ "CHOOSE_MODEL = \"gpt2-small (124M)\"\n",
+ "BASE_CONFIG.update(model_configs[CHOOSE_MODEL])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "e7b22375-6fac-4e90-9063-daa4de86c778",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "import urllib.request\n",
+ "from safetensors.torch import load_file\n",
+ "\n",
+ "URL_DIR = {\n",
+ " \"gpt2-small (124M)\": \"gpt2\", # works ok\n",
+ " \"gpt2-medium (355M)\": \"gpt2-medium\", # this file seems to have issues via `generate`\n",
+ " \"gpt2-large (774M)\": \"gpt2-large\", # works ok\n",
+ " \"gpt2-xl (1558M)\": \"gpt2-xl\" # works ok\n",
+ "}\n",
+ "\n",
+ "url = f\"https://huggingface.co/openai-community/{URL_DIR[CHOOSE_MODEL]}/resolve/main/model.safetensors\"\n",
+ "output_file = f\"model-{URL_DIR[CHOOSE_MODEL]}.safetensors\"\n",
+ "\n",
+ "# Download file\n",
+ "if not os.path.exists(output_file):\n",
+ " urllib.request.urlretrieve(url, output_file)\n",
+ "\n",
+ "# Load file\n",
+ "state_dict = load_file(output_file)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "4e2a4cf4-a54e-4307-9141-fb9f288e4dfa",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def assign(left, right):\n",
+ " if left.shape != right.shape:\n",
+ " raise ValueError(f\"Shape mismatch. Left: {left.shape}, Right: {right.shape}\")\n",
+ " return torch.nn.Parameter(right.detach())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "75be3077-f141-44bb-af88-62580ffd224c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def load_weights_into_gpt(gpt, params):\n",
+ " gpt.pos_emb.weight = assign(gpt.pos_emb.weight, params[\"wpe.weight\"])\n",
+ " gpt.tok_emb.weight = assign(gpt.tok_emb.weight, params[\"wte.weight\"])\n",
+ "\n",
+ " for b in range(len(gpt.trf_blocks)):\n",
+ " q_w, k_w, v_w = torch.chunk(\n",
+ " params[f\"h.{b}.attn.c_attn.weight\"], 3, axis=-1)\n",
+ " gpt.trf_blocks[b].att.W_query.weight = assign(\n",
+ " gpt.trf_blocks[b].att.W_query.weight, q_w.T)\n",
+ " gpt.trf_blocks[b].att.W_key.weight = assign(\n",
+ " gpt.trf_blocks[b].att.W_key.weight, k_w.T)\n",
+ " gpt.trf_blocks[b].att.W_value.weight = assign(\n",
+ " gpt.trf_blocks[b].att.W_value.weight, v_w.T)\n",
+ "\n",
+ " q_b, k_b, v_b = torch.chunk(\n",
+ " params[f\"h.{b}.attn.c_attn.bias\"], 3, axis=-1)\n",
+ " gpt.trf_blocks[b].att.W_query.bias = assign(\n",
+ " gpt.trf_blocks[b].att.W_query.bias, q_b)\n",
+ " gpt.trf_blocks[b].att.W_key.bias = assign(\n",
+ " gpt.trf_blocks[b].att.W_key.bias, k_b)\n",
+ " gpt.trf_blocks[b].att.W_value.bias = assign(\n",
+ " gpt.trf_blocks[b].att.W_value.bias, v_b)\n",
+ "\n",
+ " gpt.trf_blocks[b].att.out_proj.weight = assign(\n",
+ " gpt.trf_blocks[b].att.out_proj.weight,\n",
+ " params[f\"h.{b}.attn.c_proj.weight\"].T)\n",
+ " gpt.trf_blocks[b].att.out_proj.bias = assign(\n",
+ " gpt.trf_blocks[b].att.out_proj.bias,\n",
+ " params[f\"h.{b}.attn.c_proj.bias\"])\n",
+ "\n",
+ " gpt.trf_blocks[b].ff.layers[0].weight = assign(\n",
+ " gpt.trf_blocks[b].ff.layers[0].weight,\n",
+ " params[f\"h.{b}.mlp.c_fc.weight\"].T)\n",
+ " gpt.trf_blocks[b].ff.layers[0].bias = assign(\n",
+ " gpt.trf_blocks[b].ff.layers[0].bias,\n",
+ " params[f\"h.{b}.mlp.c_fc.bias\"])\n",
+ " gpt.trf_blocks[b].ff.layers[2].weight = assign(\n",
+ " gpt.trf_blocks[b].ff.layers[2].weight,\n",
+ " params[f\"h.{b}.mlp.c_proj.weight\"].T)\n",
+ " gpt.trf_blocks[b].ff.layers[2].bias = assign(\n",
+ " gpt.trf_blocks[b].ff.layers[2].bias,\n",
+ " params[f\"h.{b}.mlp.c_proj.bias\"])\n",
+ "\n",
+ " gpt.trf_blocks[b].norm1.scale = assign(\n",
+ " gpt.trf_blocks[b].norm1.scale,\n",
+ " params[f\"h.{b}.ln_1.weight\"])\n",
+ " gpt.trf_blocks[b].norm1.shift = assign(\n",
+ " gpt.trf_blocks[b].norm1.shift,\n",
+ " params[f\"h.{b}.ln_1.bias\"])\n",
+ " gpt.trf_blocks[b].norm2.scale = assign(\n",
+ " gpt.trf_blocks[b].norm2.scale,\n",
+ " params[f\"h.{b}.ln_2.weight\"])\n",
+ " gpt.trf_blocks[b].norm2.shift = assign(\n",
+ " gpt.trf_blocks[b].norm2.shift,\n",
+ " params[f\"h.{b}.ln_2.bias\"])\n",
+ "\n",
+ " gpt.final_norm.scale = assign(gpt.final_norm.scale, params[\"ln_f.weight\"])\n",
+ " gpt.final_norm.shift = assign(gpt.final_norm.shift, params[\"ln_f.bias\"])\n",
+ " gpt.out_head.weight = assign(gpt.out_head.weight, params[\"wte.weight\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "cda44d37-92c0-4c19-a70a-15711513afce",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import torch\n",
+ "from previous_chapters import GPTModel\n",
+ "\n",
+ "\n",
+ "gpt = GPTModel(BASE_CONFIG)\n",
+ "\n",
+ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
+ "load_weights_into_gpt(gpt, state_dict)\n",
+ "gpt.to(device);"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "4ddd0d51-3ade-4890-9bab-d63f141d095f",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Output text:\n",
+ " Every effort moves forward, but it's not enough.\n",
+ "\n",
+ "\"I'm not going to sit here and say, 'I'm not going to do this,'\n"
+ ]
+ }
+ ],
+ "source": [
+ "import tiktoken\n",
+ "from previous_chapters import generate, text_to_token_ids, token_ids_to_text\n",
+ "\n",
+ "torch.manual_seed(123)\n",
+ "\n",
+ "tokenizer = tiktoken.get_encoding(\"gpt2\")\n",
+ "\n",
+ "token_ids = generate(\n",
+ " model=gpt.to(device),\n",
+ " idx=text_to_token_ids(\"Every effort moves\", tokenizer).to(device),\n",
+ " max_new_tokens=30,\n",
+ " context_size=BASE_CONFIG[\"context_length\"],\n",
+ " top_k=1,\n",
+ " temperature=1.0\n",
+ ")\n",
+ "\n",
+ "print(\"Output text:\\n\", token_ids_to_text(token_ids, tokenizer))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.4"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/ch05/02_alternative_weight_loading/weight-loading-hf-transformers.ipynb b/ch05/02_alternative_weight_loading/weight-loading-hf-transformers.ipynb
index 0f92a87..f267baf 100644
--- a/ch05/02_alternative_weight_loading/weight-loading-hf-transformers.ipynb
+++ b/ch05/02_alternative_weight_loading/weight-loading-hf-transformers.ipynb
@@ -293,7 +293,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.11"
+ "version": "3.11.4"
}
},
"nbformat": 4,