license: mit
tags:
- code
pipeline_tag: text-generation tags:
- code model-index:
- name: VeriGen
results:
- task: type: text-generation dataset: type: name:
extra_gated_prompt: >-
Model License Agreement
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license
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VeriGen
Table of Contents
Dataset Summary
The dataset comprises Verilog modules as entries. The entries were retrieved from the GitHub dataset on BigQuery.
For training [models (https://huggingface.co/shailja/fine-tuned-codegen-2B-Verilog)], we filtered entries with no of characters exceeding 20000 and duplicates (exact duplicates ignoring whitespaces).
Paper: Benchmarking Large Language Models for Automated Verilog RTL Code Generation
Point of Contact: contact@shailja
Languages: Verilog (Hardware Description Language)
Data Splits
The dataset only contains a train split.
Use
# pip install datasets
from datasets import load_dataset
ds = load_dataset("shailja/Verilog_GitHub", streaming=True, split="train")
print(next(iter(ds)))
#OUTPUT:
Intended Use
The dataset consists of source code from a range of GitHub repositories. As such, they can potentially include non-compilable, low-quality, and vulnerable code.
Attribution & Other Requirements
The pretraining dataset of the model was not filtered for permissive licenses only. Nevertheless, the model can generate source code verbatim from the dataset. The code's license might require attribution and/or other specific requirements that must be respected.
License
The dataset is licensed under the BigCode OpenRAIL-M v1 license agreement. You can find the full agreement here.
Citation
@misc{https://doi.org/10.48550/arxiv.2212.11140,
doi = {10.48550/ARXIV.2212.11140},
url = {https://arxiv.org/abs/2212.11140},
author = {Thakur, Shailja and Ahmad, Baleegh and Fan, Zhenxing and Pearce, Hammond and Tan, Benjamin and Karri, Ramesh and Dolan-Gavitt, Brendan and Garg, Siddharth},
title = {Benchmarking Large Language Models for Automated Verilog RTL Code Generation},
publisher = {arXiv},
year = {2022},
copyright = {arXiv.org perpetual, non-exclusive license}
}