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https://github.com/rasbt/LLMs-from-scratch.git
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Add backup url for Spam Dataset (#543)
* Add backup url for Spam Dataset * import urllib * fix url
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@ -48,12 +48,12 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"matplotlib version: 3.7.2\n",
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"numpy version: 1.25.2\n",
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"tiktoken version: 0.5.1\n",
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"torch version: 2.2.2\n",
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"tensorflow version: 2.15.0\n",
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"pandas version: 2.0.3\n"
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"matplotlib version: 3.10.0\n",
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"numpy version: 2.0.2\n",
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"tiktoken version: 0.9.0\n",
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"torch version: 2.6.0\n",
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"tensorflow version: 2.18.0\n",
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"pandas version: 2.2.3\n"
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]
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}
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],
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@ -190,6 +190,7 @@
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}
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],
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"source": [
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"import urllib\n",
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"from pathlib import Path\n",
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"import pandas as pd\n",
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"from previous_chapters import (\n",
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@ -204,7 +205,13 @@
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"extracted_path = \"sms_spam_collection\"\n",
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"data_file_path = Path(extracted_path) / \"SMSSpamCollection.tsv\"\n",
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"\n",
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"download_and_unzip_spam_data(url, zip_path, extracted_path, data_file_path)\n",
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"try:\n",
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" download_and_unzip_spam_data(url, zip_path, extracted_path, data_file_path)\n",
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"except urllib.error.HTTPError:\n",
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" print(\"UCI Machine Learning Repository (https://archive.ics.uci.edu)\"\n",
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" \" temporary unavailable. Using backup URL.\")\n",
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" url = \"https://f001.backblazeb2.com/file/LLMs-from-scratch/sms%2Bspam%2Bcollection.zip\"\n",
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" download_and_unzip_spam_data(url, zip_path, extracted_path, data_file_path)\n",
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"\n",
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"df = pd.read_csv(data_file_path, sep=\"\\t\", header=None, names=[\"Label\", \"Text\"])\n",
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"balanced_df = create_balanced_dataset(df)\n",
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@ -50,7 +50,7 @@
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"text": [
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"matplotlib version: 3.10.0\n",
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"numpy version: 2.0.2\n",
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"tiktoken version: 0.8.0\n",
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"tiktoken version: 0.9.0\n",
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"torch version: 2.6.0\n",
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"tensorflow version: 2.18.0\n",
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"pandas version: 2.2.3\n"
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@ -167,7 +167,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 2,
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"id": "def7c09b-af9c-4216-90ce-5e67aed1065c",
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"metadata": {
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"colab": {
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@ -181,7 +181,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"sms_spam_collection/SMSSpamCollection.tsv already exists. Skipping download and extraction.\n"
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"File downloaded and saved as sms_spam_collection/SMSSpamCollection.tsv\n"
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]
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}
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],
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@ -215,7 +215,13 @@
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" os.rename(original_file_path, data_file_path)\n",
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" print(f\"File downloaded and saved as {data_file_path}\")\n",
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"\n",
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"download_and_unzip_spam_data(url, zip_path, extracted_path, data_file_path)"
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"try:\n",
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" download_and_unzip_spam_data(url, zip_path, extracted_path, data_file_path)\n",
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"except urllib.error.HTTPError:\n",
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" print(\"UCI Machine Learning Repository (https://archive.ics.uci.edu)\"\n",
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" \" temporary unavailable. Using backup URL.\")\n",
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" url = \"https://f001.backblazeb2.com/file/LLMs-from-scratch/sms%2Bspam%2Bcollection.zip\"\n",
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" download_and_unzip_spam_data(url, zip_path, extracted_path, data_file_path) "
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]
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},
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{
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@ -276,7 +276,16 @@ if __name__ == "__main__":
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extracted_path = "sms_spam_collection"
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data_file_path = Path(extracted_path) / "SMSSpamCollection.tsv"
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download_and_unzip_spam_data(url, zip_path, extracted_path, data_file_path, test_mode=args.test_mode)
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try:
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download_and_unzip_spam_data(
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url, zip_path, extracted_path, data_file_path, test_mode=args.test_mode
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)
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except urllib.error.HTTPError:
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backup_url = "https://f001.backblazeb2.com/file/LLMs-from-scratch/sms%2Bspam%2Bcollection.zip"
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download_and_unzip_spam_data(
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backup_url, zip_path, extracted_path, data_file_path, test_mode=args.test_mode
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)
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df = pd.read_csv(data_file_path, sep="\t", header=None, names=["Label", "Text"])
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balanced_df = create_balanced_dataset(df)
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balanced_df["Label"] = balanced_df["Label"].map({"ham": 0, "spam": 1})
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@ -603,7 +603,11 @@ if __name__ == "__main__":
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all_exist = all((base_path / file_name).exists() for file_name in file_names)
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if not all_exist:
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download_and_unzip(url, zip_path, extract_to, new_file_path)
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try:
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download_and_unzip(url, zip_path, extract_to, new_file_path)
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except urllib.error.HTTPError:
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backup_url = "https://f001.backblazeb2.com/file/LLMs-from-scratch/sms%2Bspam%2Bcollection.zip"
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download_and_unzip(backup_url, zip_path, extract_to, new_file_path)
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create_dataset_csvs(new_file_path)
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tokenizer = tiktoken.get_encoding("gpt2")
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@ -410,7 +410,11 @@ if __name__ == "__main__":
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all_exist = all((base_path / file_name).exists() for file_name in file_names)
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if not all_exist:
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download_and_unzip(url, zip_path, extract_to, new_file_path)
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try:
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download_and_unzip(url, zip_path, extract_to, new_file_path)
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except urllib.error.HTTPError:
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backup_url = "https://f001.backblazeb2.com/file/LLMs-from-scratch/sms%2Bspam%2Bcollection.zip"
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download_and_unzip(backup_url, zip_path, extract_to, new_file_path)
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create_dataset_csvs(new_file_path)
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if args.use_attention_mask.lower() == "true":
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