Update README.md

README.md

@@ -3211,17 +3211,34 @@ configs:
   - split: train
     path: data/WebAssembly/train-*
 ---
-# DISCLAIMER 
-
-This represents only a subset of the final dataset (taking into account the new HuggingFace LFS storage limits). The complete dataset will be released following the camera-ready submission of our paper.
-
 # The Heap Dataset
 
 We develop **The Heap**, a new contamination-free multilingual code dataset comprising 57 languages, which facilitates LLM evaluation reproducibility. The reproduction packge can be found [here](https://anonymous.4open.science/r/heap-forge/README.md).
 
 # Is your code in The Heap? 
 
-An opt-out mechanism will be provided for the final release of the dataset. 
+ If you would like to have your data removed from the dataset, follow the instructions on [GitHub](https://github.com/AISE-TUDelft/The-Heap-opt-out).
+
+# Usage 
+
+Using the Datasets API, our dataset can be used as follows:
+
+```python
+from datasets import load_dataset
+
+dataset_name = 'redpajama'
+language = 'Python'
+
+ds = load_dataset(
+    "AISE-TUDelft/the-heap",
+    f"{language}",
+    split="train",
+    num_proc=16
+)
+
+ds = ds.filter(lambda x: not x[f'exact_duplicates_{dataset_name}'] and not x[f'near_duplicates_{dataset_name}'])
+
+```
 
 # Collection
 
@@ -3332,19 +3349,23 @@ The final dataset structure is shown in the example below.
 
 ```json
 {
+    "id": 538,
     "file_name": "Font.java",
     "file_path": ".../lateralgm/resources/Font.java",
     "content": "*/ package org.lateralgm.resources; import java.util.EnumMap; import org.lateralgm.main.Prefs; ...",
-    "file_size": 1,985,
+    "size": 1,985,
     "language": "Java",
     "extension": ".java",
+    "total_lines": 3,835,
+    "avg_line_length": 29,834,
+    "max_line_length": 567,
+    "alphanum_fraction": 0,645,
     "repo_name": "lwizchz/GameMaker-HTML5-Player",
     "repo_stars": 22,
     "repo_forks": 9,
     "repo_open_issues": 0,
-    "repo_created_at": "2011-09-10T16:05:20Z",
-    "repo_pushed_at": "2013-05-06T23:00:17Z",
-    "sha": "00046809b218b2c058f4be7...",
+    "repo_license": "GPL-3.0",
+    "repo_extraction_date": "9/19/2024, 2:48:21 PM (Europe/Amsterdam)"
     "exact_duplicates_stackv1": False,
     "exact_duplicates_stackv2": True,
     "near_duplicates_stackv1": True,
@@ -3357,18 +3378,23 @@ The final dataset structure is shown in the example below.
 
 ### Dataset Fields
 
+- **id**: unique ID of the file
 - **file_name**: name of the file extracted from its repo
 - **file_path**: path to the file in its repo
 - **content**: content of the file
-- **file_size**: size of the file
+- **size**: size of the file
 - **language**: language of the file
+- **total_lines**: number of total lines of the file
+- **avg_line_length**: average line length of the file
+- **max_line_length**: max line length of the file
+- **alphanum_fraction**: alphanumeric fraction of the file
 - **extension**: language extension of the file
 - **repo_name**: complete name of the file's repo
 - **repo_stars**: number of stars of the file's repo
 - **repo_forks**: number of forks of the file's repo
 - **repo_open_issues**: number of open issues of the file's repo at the extraction date
-- **repo_created_at**: creation date of the file's repo
-- **repo_pushed_at**: date of the most recent push to the file's repo until the extraction date
+- **repo_license**: license of the file's repo
+- **repo_extraction_date**: extraction date of file's repo
 - **exact_duplicates_pubdataset**: boolean flag stating if there are any exact duplicate files found against another public dataset (The Stackv2, The Stack, RedPajama, GithubCode, CodeParrot)
 - **near_duplicates_pubdataset**: boolean flag stating if there are any near duplicate files found against another public dataset (The Stackv2, The Stack, RedPajama, GithubCode, CodeParrot)
 
@@ -3435,24 +3461,3 @@ The distribution of the languages in The Heap is presented in the table below. T
 | Vue | 14,858 | 457,605 | 321,502 |
 | WebAssembly | 68 | 834 | 544 |
 | Total | 733,564 | 96,945,943 | 32,666,778 |
-
-# Usage 
-
-Using the Datasets API, our dataset can be used as follows:
-
-```python
-from datasets import load_dataset
-
-dataset_name = 'redpajama'
-language = 'Python'
-
-ds = load_dataset(
-    "AISE-TUDelft/the-heap",
-    f"{language}",
-    split="train",
-    num_proc=16
-)
-
-ds = ds.filter(lambda x: not x[f'exact_duplicates_{dataset_name}'] and not x[f'near_duplicates_{dataset_name}'])
-
-```