---
license: apache-2.0
datasets:
- code_search_net
language:
- code
tags:
- code tokenizer
- python tokenizer
- GPT-2
---
**Model Card: (TEST) code-search-net-tokenizer**

**Model Description:**

The Code Search Net Tokenizer is a custom tokenizer specifically trained for tokenizing Python code snippets. It has been trained on a large corpus of Python code snippets from the CodeSearchNet dataset using the GPT-2 model as a starting point. The goal of this tokenizer is to effectively tokenize Python code for use in various natural language processing and code-related tasks.

**Model Details:**

 - Name: Code Search Net Tokenizer
 - Model Type: Custom Tokenizer
 - Language: Python

**Training Data:**

The tokenizer was trained on a corpus of Python code snippets from the CodeSearchNet dataset. The dataset consists of various Python code examples collected from open-source repositories on GitHub. The tokenizer has been fine-tuned on this dataset to create a specialized vocabulary that captures the unique syntax and structure of Python code.

**Tokenizer Features:**

 - The Code Search Net Tokenizer offers the following features:

 - Tokenization of Python code: The tokenizer can effectively split Python code snippets into individual tokens, making it suitable for downstream tasks that involve code processing and understanding.

**Usage:**

You can use the `code-search-net-tokenizer` to preprocess code snippets and convert them into numerical representations suitable for feeding into language models.

**Limitations:**

The `code-search-net-tokenizer` is specifically tailored to code-related text data and may not be suitable for general text tasks. It may not perform optimally for natural language text outside the programming context.