Create README.md
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README.md
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---
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language:
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- code
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- en
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multilinguality:
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- multiprogramming languages
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task_categories:
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- text-generation
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dataset_info:
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features:
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- name: identifier
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dtype: string
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- name: return_type
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dtype: string
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- name: repo
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dtype: string
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- name: path
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dtype: string
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- name: language
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dtype: string
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- name: code
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dtype: string
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- name: code_tokens
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dtype: string
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- name: original_docstring
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dtype: string
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- name: comment
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dtype: string
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- name: docstring_tokens
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dtype: string
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- name: docstring
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dtype: string
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- name: original_string
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dtype: string
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splits:
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- name: python
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num_bytes: 30797754227
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num_examples: 9893858
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- name: java
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num_bytes: 23130202517
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num_examples: 7886299
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- name: javascript
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num_bytes: 6833869001
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num_examples: 2562158
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- name: php
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num_bytes: 13072500520
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num_examples: 5455989
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- name: c_sharp
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num_bytes: 11144245789
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num_examples: 4011467
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- name: c
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num_bytes: 6205820571
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num_examples: 1978551
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- name: cpp
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num_bytes: 6228306797
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num_examples: 1934958
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- name: go
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num_bytes: 11339059495
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num_examples: 5649158
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- name: rust
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num_bytes: 2661037428
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num_examples: 1076588
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- name: ruby
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num_bytes: 1224195690
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num_examples: 544867
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download_size: 26404353470
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dataset_size: 112636992035
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pretty_name: The Vault
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viewer: true
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---
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks](#supported-tasks)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Statistics](#dataset-statistics)
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- [Usage](#usage)
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- [Additional Information](#additional-information)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Repository:** [FSoft-AI4Code/TheVault](https://github.com/FSoft-AI4Code/TheVault)
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- **Paper:** The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation
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- **Contact:** [email protected]
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- **Website:** https://www.fpt-aicenter.com/ai-residency/
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![thevault-logo](https://raw.githubusercontent.com/FSoft-AI4Code/TheVault/main/assets/thevault-title.png)
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## Dataset Summary
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The Vault is a multilingual code-text dataset with over 40 million pairs covering 10 popular programming languages. It is the largest corpus containing parallel code-text data. By building upon [The Stack](https://huggingface.co/datasets/bigcode/the-stack), a massive raw code sample collection, the Vault offers a comprehensive and clean resource for advancing research in code understanding and generation. It also addresses these issues by providing a large, high-quality dataset that includes code-text pairs at multiple levels, such as class and inline-level, in addition to the function level. The Vault can serve many purpose at multiple levels.
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## Supported Tasks
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The Vault can be used for pretraining LLMs or downstream code-text interaction tasks. A number of tasks can be constructed using The Vault such as *code summarization*, *text-to-code generation* and *code search*.
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## Languages
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The natural language text (docstring) is in English.
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10 programming languages are supported in The Vault: `Python`, `Java`, `JavaScript`, `PHP`, `C`, `C#`, `C++`, `Go`, `Ruby`, `Rust`
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## Dataset Structure
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### Data Instances
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*a. Function-level and Class-level*
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```
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{
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"identifier": "REDUCE",
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"return_type": "<not_specify>"
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"repo": "irshadbhat/sndpcs",
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"path": "arc_eager.py",
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"language": "Python",
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"code": "def REDUCE(self, configuration, label=None):\n b0 = configuration.b0\n configuration.stack.pop()",
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"code_tokens": "def REDUCE ( self , configuration , label = None ) : b0 = configuration . b0 configuration . stack . pop ( )",
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"original_docstring": "\n pops the top of the stack if it has got its head.\n ",
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"comment": "\"\"\"\n pops the top of the stack if it has got its head.\n \"\"\"",
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"docstring_tokens": "pops the top of the stack if it has got its head .",
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"docstring": "pops the top of the stack if it has got its head."
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}
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```
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### Data Fields
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Data fields for function level:
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- **repo** (string): the owner/repo
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- **path** (string): the full path to the original file
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- **language** (string): the programming language
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- **identifier** (string): the function or method name
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- **return_type** (string): the type returned by the function
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- **original_string** (string): original version of function/class node
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- **original_docstring** (string): the raw string before tokenization or parsing
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- **code** (string): the part of the original that is code
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- **code_tokens** (string): tokenized version of `code`, separated by whitespace
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- **short_docstring** (string): short, brief summarization (first line of the docstring)
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- **short_docstring_tokens** (string): tokenized version of `short_docstring`, separated by whitespace
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- **docstring** (string): the top-level comment or docstring (docstring version without param’s doc, return, exception, etc)
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- **docstring_tokens** tokenized version of docstring, separated by whitespace
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- **comment** (string): comment (line) inside the function/class, separated by `$SEP$` token
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- **parameters** (dict): Dictionary of parameters and its type (type can be None)
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- **docstring_params** (dict): Dictionary of the parsed information from docstring
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Due to the limiration huggingface data structure we do not contain **parameters** and **docstring_params** field in this repo. The detail of data fields can be found in [The Vault data format](https://github.com/FSoft-AI4Code/TheVault/blob/main/data/README.md) and the full dataset version can be downloaded at [here](https://github.com/FSoft-AI4Code/TheVault/)
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### Data Splits
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In this repo, The Vault is divided into 10 subsets based on the supported programming languages. The statistic for each language is illustrated in the following section.
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## Dataset Statistics
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- Compare to other benchmarks
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| Dataset | #Language | #Code-text pair |
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|:--------------------------|----------:|-----------------:|
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| PyMT5 | 1 | ≈ 7,700,000 |
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| CoDesc | 1 | 4,211,516 |
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| CodeSearchNet | 6 | 2,326,976 |
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| CodeSearchNet (CodeXGLUE) | 6 | 1,005,474 |
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| Deepcom | 1 | 424,028 |
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| CONCODE | 1 | 2,184,310 |
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| Funcom | 1 | 2,149,121 |
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| CodeT5 | 8 | 3,158,313 |
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| **The Vault** | **10** | **40,993,893** |
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- Statistic for each language in The Vault
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| Language | #Code-text pair | #Repository |
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|:-----------|-----------------:|------------:|
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| Python | 9,893,858 | 628,069 |
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| PHP | 5,455,989 | 439,514 |
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| JavaScript | 2,562,158 | 355,761 |
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| Java | 7,886,299 | 321,129 |
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| C# | 4,011,467 | 150,657 |
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| C++ | 1,934,958 | 116,897 |
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| C | 1,978,551 | 88,556 |
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| Go | 5,649,158 | 241,238 |
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| Rust | 1,076,588 | 68,615 |
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| Ruby | 544,867 | 61,804 |
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## Usage
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You can load The Vault dataset using datasets library: ```pip install datasets```
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```python
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from datasets import load_dataset
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# Load full function level dataset (40M samples)
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ds = load_dataset("Fsoft-AIC/the-vault-function")
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# Load function level train/validation/test set
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ds = load_dataset("Fsoft-AIC/the-vault-function", split_set=["train"])
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# Load "small" (or "medium", "large") function level training set
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ds = load_dataset("Fsoft-AIC/the-vault-function", split_set=["train/small"])
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# specific language (e.g. Golang)
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ds = load_dataset("Fsoft-AIC/the-vault-function", split_set=["train"], languages=['Go'])
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```
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## Additional information
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### Licensing Information
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### Citation Information
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```
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@misc{manh2023vault,
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title={The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation},
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author={Dung Nguyen Manh and Nam Le Hai and Anh T. V. Dau and Anh Minh Nguyen and Khanh Nghiem and Jin Guo and Nghi D. Q. Bui},
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year={2023},
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}
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```
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### Contributions
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