Upload cleaning_code.py

cleaning_code.py

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+# -*- coding: utf-8 -*-
+"""scratchpad
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/notebooks/empty.ipynb
+"""
+
+pip install -q datasets transformers
+
+from datasets import load_dataset
+
+dataset = load_dataset("tau/scrolls", "qmsum")
+
+dataset
+
+!pip install clean-text[gpl] -q
+from cleantext import clean
+
+train_df = dataset["train"].to_pandas().convert_dtypes()
+val_df = dataset["validation"].to_pandas().convert_dtypes()
+test_df = dataset["test"].to_pandas().convert_dtypes()
+
+from tqdm.auto import tqdm 
+
+tqdm.pandas()
+
+train_df["input"] = train_df["input"].progress_apply(clean, lower=False, no_urls=True, no_emails=True)
+val_df["input"] = val_df["input"].progress_apply(clean, lower=False, no_urls=True, no_emails=True)
+test_df["input"] = test_df["input"].progress_apply(clean, lower=False, no_urls=True, no_emails=True)
+
+train_df["output"] = train_df["output"].progress_apply(clean, lower=False, no_urls=True, no_emails=True)
+val_df["output"] = val_df["output"].progress_apply(clean, lower=False, no_urls=True, no_emails=True)
+test_df["output"] = test_df["output"].progress_apply(clean, lower=False, no_urls=True, no_emails=True)
+
+import re
+import re
+def fix_punct_whitespace(text: str) -> str:
+    # Fix spaces around apostrophes
+    text = re.sub(r"([a-zA-Z])\s?'\s?([a-zA-Z])", r"\1'\2", text)
+
+    # Remove spaces before punctuation marks (except for parentheses)
+    text = re.sub(r"\s+([.,;:!?])", r"\1", text)
+
+    # Add a space after punctuation marks (except for parentheses) if missing
+    text = re.sub(r"([.,;:!?])(?=[^\s])", r"\1 ", text)
+
+    # Handle spaces around parentheses
+    text = re.sub(r"\s?\(\s?", r" (", text)
+    text = re.sub(r"\s?\)\s?", r")", text)
+
+    # Add a space after a closing parenthesis if:
+    # followed by a word or opening parenthesis
+    text = re.sub(r"\)(?=[^\s.,;:!?])", r") ", text)
+
+    # Handle spaces around quotation marks
+    text = re.sub(r'\s?"', r'"', text)
+    text = re.sub(r'"\s?', r'" ', text)
+
+    # Handle spaces around single quotes
+    text = re.sub(r"\s?'", r"'", text)
+    text = re.sub(r"'\s?", r"' ", text)
+
+    # Handle comma in numbers
+    text = re.sub(r"(\d),\s+(\d)", r"\1,\2", text)
+
+    return text.replace("' ", "'")
+
+train_df["input"] = train_df["input"].progress_apply(fix_punct_whitespace)
+val_df["input"] = val_df["input"].progress_apply(fix_punct_whitespace)
+test_df["input"] = test_df["input"].progress_apply(fix_punct_whitespace)
+
+train_df["output"] = train_df["output"].progress_apply(fix_punct_whitespace)
+val_df["output"] = val_df["output"].progress_apply(fix_punct_whitespace)
+test_df["output"] = test_df["output"].progress_apply(fix_punct_whitespace)
+
+train_df.head(2)
+
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("pszemraj/long-t5-tglobal-xl-16384-book-summary-8bit")
+
+def get_token_count(text:str):
+    if len(text) < 1:
+        return 0
+    else:
+        return len(tokenizer.encode(text, truncation=False, padding=False))
+
+get_token_count("ayyy waddup my g")
+
+train_df["input_token_count"] = train_df["input"].progress_apply(get_token_count)
+val_df["input_token_count"] = val_df["input"].progress_apply(get_token_count)
+test_df["input_token_count"] = test_df["input"].progress_apply(get_token_count)
+
+train_df["output_token_count"] = train_df["output"].progress_apply(get_token_count)
+val_df["output_token_count"] = val_df["output"].progress_apply(get_token_count)
+test_df["output_token_count"] = test_df["output"].progress_apply(get_token_count)
+
+
+
+train_df.describe()
+
+"""# New Section"""
+
+# Commented out IPython magic to ensure Python compatibility.
+# %%bash
+# curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
+# apt-get install git-lfs -q
+# git lfs install
+
+!pip install -U -q transformers accelerate
+from huggingface_hub import notebook_login
+notebook_login()
+
+# Commented out IPython magic to ensure Python compatibility.
+# %%bash
+# 
+# git lfs install
+# git clone https://huggingface.co/datasets/pszemraj/qmsum-cleaned
+
+from pathlib import Path 
+
+target = Path.cwd() / 'qmsum-cleaned'
+target.exists()
+
+train_df.to_parquet(target / 'train.parquet')
+val_df.to_parquet(target / 'validation.parquet')
+test_df.to_parquet(target/ 'test.parquet')
+!ls $target
+
+# Commented out IPython magic to ensure Python compatibility.
+# %cd $target
+!git pull
+!git lfs install && git lfs track *.parquet
+!git add . && git commit -a -m add_cleaned
+!git push
+# %cd ..
+
+# Commented out IPython magic to ensure Python compatibility.
+# %%bash
+# git config --global user.email "[email protected]"
+# git config --global user.name "colab"
+