README.md

metadata

task_categories:
  - text-generation
configs:
  - config_name: ir1xor1
    data_files:
      - split: train
        path: data/ir1xor1/train*
      - split: test
        path: data/ir1xor1/test*
  - config_name: ir1xor3
    data_files:
      - split: train
        path: data/ir1xor3/train*
      - split: test
        path: data/ir1xor3/test*
  - config_name: ir1xor4
    data_files:
      - split: train
        path: data/ir1xor4/train*
      - split: test
        path: data/ir1xor4/test*
  - config_name: ir2xor2
    data_files:
      - split: train
        path: data/ir2xor2/train*
      - split: test
        path: data/ir2xor2/test*
  - config_name: ir3xor2
    data_files:
      - split: train
        path: data/ir3xor2/train*
      - split: test
        path: data/ir3xor2/test*
  - config_name: ir4xor2
    data_files:
      - split: train
        path: data/ir4xor2/train*
      - split: test
        path: data/ir4xor2/test*
  - config_name: ir4xor2-deepseek
    data_files:
      - split: train
        path: data/ir4xor2-deepseek/train*
      - split: test
        path: data/ir4xor2-deepseek/test*
dataset_info:
  - config_name: default
    features:
      - name: input
        dtype: string
      - name: output
        dtype: string
    splits:
      - name: train
      - name: test
language:
  - code
size_categories:
  - 10K<n<100K

RepairLLaMA - Datasets

Contains the processed fine-tuning datasets for RepairLLaMA.

Instructions to explore the dataset

To load the dataset, you must define which revision (i.e., which input/output representation pair) you want to load.

from datasets import load_dataset

# Load ir1xor1
dataset = load_dataset("ASSERT-KTH/repairllama-datasets", "ir1xor1")
# Load irXxorY
dataset = load_dataset("ASSERT-KTH/repairllama-datasets", "irXxorY")

Citation

If you use RepairLLaMA in academic research, please cite "RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair", Technical report, arXiv 2312.15698, 2023.

@techreport{repairllama2023,
  title={RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair},
  author={Silva, Andr{\'e} and Fang, Sen and Monperrus, Martin},
  url = {http://arxiv.org/abs/2312.15698},
  number = {2312.15698},
  institution = {arXiv},
}