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@@ -141,23 +141,24 @@ 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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- - **license** (string): license in the repo
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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 limitation of the huggingface data structure, we do not contain **parameters** and **docstring_params** fields 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 [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 5 subsets, where three training versions are split based on dataset size, and the remains are validation set and test set (20,000 samples in each). The statistic for each language is illustrated in the following section.
@@ -219,6 +220,8 @@ for sample in iter(data['train']):
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  print(sample)
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  ```
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  ## Additional information
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  ### Licensing Information
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  [More information needed]
 
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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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+ - **license** (list): license in the repo
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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** (list): tokenized version of `code`
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  - **short_docstring** (string): short, brief summarization (first line of the docstring)
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+ - **short_docstring_tokens** (list): tokenized version of `short_docstring
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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** (list): tokenized version of docstring
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+ - **comment** (list): list of comments (line) inside the function/class
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+ - **parameters** (list): List 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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+ See [here](https://github.com/FSoft-AI4Code/TheVault/blob/main/data/README.md) for more details and examples.
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+
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  ### Data Splits
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  In this repo, The Vault is divided into 5 subsets, where three training versions are split based on dataset size, and the remains are validation set and test set (20,000 samples in each). The statistic for each language is illustrated in the following section.
 
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  print(sample)
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  ```
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+ A back up dataset can be downloaded in azure storage. See [Download The Vault from Azure blob storage](https://github.com/FSoft-AI4Code/TheVault/blob/main/README.md#download-data-from-azure-blob-storage)
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+
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  ## Additional information
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  ### Licensing Information
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  [More information needed]