Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
Tags:
code
License:
metadata
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])