README.md

---
license: apache-2.0
task_categories:
- text-generation
language:
- en
tags:
- code
pretty_name: vgen_cpp
size_categories:
- 1K<n<10K
---

# Dataset Card for Opencores

In the process of continual pre-training, we utilized the publicly available VGen dataset. 
VGen aggregates Verilog repositories from GitHub, systematically filters out duplicates and excessively large files, and retains only those files containing \texttt{module} and \texttt{endmodule} statements. 

We also incorporated the CodeSearchNet dataset \cite{codesearchnet}, which contains approximately 40MB function codes and their documentation. 

## Dataset Features

- text (string): The pretraining corpus: nature language and Verilog/C code.

## Loading the dataset

```
from datasets import load_dataset

ds = load_dataset("LLM-EDA/vgen_cpp", split="train")
print(ds[0])
```

## Citation