class_docstr: The Pile corpus from this paper:
  https://arxiv.org/pdf/2101.00027.pdf
code: def get_instances(self) -> List[Instance]:
      # Download the raw data
      data_path = os.path.join(self.output_path, "data")
      ensure_file_downloaded(
          source_url="https://the-eye.eu/public/AI/pile/test.jsonl.zst",
          target_path=data_path,
          unpack=True,
      )
  
      subset_path = os.path.join(self.output_path, self.subset + ".csv")
  
      # If the target subset does not exist, load and cache all subsets to the directory
      if not os.path.exists(subset_path):
          self.load_and_cache_all_subsets()
  
      # Read all the instances
      instances = []
      hlog(f"Reading {subset_path}")
      with open(subset_path, "r") as f:
          csv.field_size_limit(sys.maxsize)
          reader = csv.reader(f)
          for row in reader:
              instance = Instance(
                  input=Input(text=row[0]),
                  references=[],
                  split=TEST_SPLIT,
              )
              instances.append(instance)
  
      # Load the subsample indices
      # Short names of the datasets
      DATASET_NAMES_DICT = {
          "Github": "github",
          "ArXiv": "arxiv",
          "Wikipedia (en)": "wikipedia",
          "OpenSubtitles": "opensubtitles",
          "OpenWebText2": "openwebtext2",
          "Gutenberg (PG-19)": "gutenberg",
          "DM Mathematics": "dm-mathematics",
          "Enron Emails": "enron",
          "Books3": "bibliotik",
          "PubMed Abstracts": "pubmed-abstracts",
          "YoutubeSubtitles": "youtubesubtitles",
          "HackerNews": "hackernews",
          "Pile-CC": "commoncrawl",
          "EuroParl": "europarl",
          "USPTO Backgrounds": "uspto",
          "FreeLaw": "freelaw",
          "NIH ExPorter": "nih-exporter",
          "StackExchange": "stackexchange",
          "PubMed Central": "pubmed-central",
          "Ubuntu IRC": "ubuntu-irc",
          "BookCorpus2": "bookcorpus",
          "PhilPapers": "philpapers",
      }
  
      # These datasets were too small (in number of docs) to split 10-ways
      DATASETS_WITHOUT_SPLIT = [
          "ubuntu-irc",
          "bookcorpus",
          "philpapers",
      ]
  
      short_name = DATASET_NAMES_DICT[self.subset]
      if short_name not in DATASETS_WITHOUT_SPLIT:
          url = (
              "https://raw.githubusercontent.com/EleutherAI/lm_perplexity/main/assets/test_subsample_indices/"
              f"{short_name}/group0.json"
          )
          indices = sorted(list(set(requests.get(url).json())))
          instances = [instances[i] for i in indices]
  
      return instances
  
file_path: H2O/h2o_hf/helm/src/helm/benchmark/scenarios/the_pile_scenario.py
imports: import os
  import json
  import csv
  import sys
  import requests
  from typing import List
  from helm.common.general import ensure_file_downloaded
  from helm.common.hierarchical_logger import hlog, htrack, htrack_block
  from .scenario import Scenario, Instance, TEST_SPLIT, Input
label_desc: Use image node_id 3 for calling the ThePileScenario obj's underlying member method code with example usage: obj.get_instances() and returns: instances