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# LLMDataParser
**LLMDataParser** is a Python library that provides parsers for benchmark datasets used in evaluating Large Language Models (LLMs). It offers a unified interface for loading and parsing datasets like **MMLU** and **GSM8k**, simplifying dataset preparation for LLM evaluation.
## Features
- **Unified Interface**: Consistent `DatasetParser` for all datasets.
- **LLM-Agnostic**: Independent of any specific language model.
- **Easy to Use**: Simple methods and built-in Python types.
- **Extensible**: Easily add support for new datasets.
## Installation
### Option 1: Using pip
You can install the package directly using `pip`. Even with only a `pyproject.toml` file, this method works for standard installations.
1. **Clone the Repository**:
```bash
git clone https://github.com/jeff52415/LLMDataParser.git
cd LLMDataParser
```
2. **Install Dependencies with pip**:
```bash
pip install .
```
### Option 2: Using Poetry
Poetry manages the virtual environment and dependencies automatically, so you don't need to create a conda environment first.
1. **Install Dependencies with Poetry**:
```bash
poetry install
```
2. **Activate the Virtual Environment**:
```bash
poetry shell
```
## Available Parsers
- **MMLUParser**: Parses the MMLU dataset.
- **GSM8kParser**: Parses the GSM8k dataset.
## Contributing
Contributions are welcome! See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contact
For questions or support, please open an issue on GitHub or contact [[email protected]](mailto:[email protected]).
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