README.md

metadata

license: mit

---

pipeline_tag: text-generation tags:

• code model-index:
• name: VeriGen results:
  • task: type: text-generation dataset: type: name:

extra_gated_prompt: >-

Model License Agreement

Please read the BigCode OpenRAIL-M license agreement before accepting it.
extra_gated_fields: I accept the above license agreement, and will use the Model complying with the set of use restrictions and sharing requirements: checkbox

VeriGen

Table of Contents

1. Dataset Summary
2. Use
3. Limitations
4. License
5. Citation

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}
}