A collection of parsers for LLM benchmark datasets
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The LLMEval Dataset Parser is a collection of parsers designed to work with large language model (LLM) benchmark datasets. It provides a standardized way to browse and parse LLM benchmark datasets, making it easier to work with diverse dataset formats and structures.
• Multiple Dataset Support: Handles various benchmark datasets for LLM evaluation.
• Metadata Extraction: Extracts detailed metadata from datasets, including task descriptions and metrics.
• Data Validation: Ensures data integrity by validating dataset structures and formats.
• Versioning Support: Manages different versions of datasets for reproducibility.
• Cross-Platform Compatibility: Works seamlessly across different operating systems and environments.
• User-Friendly Interface: Provides a simple and intuitive CLI for parsing and managing datasets.
llm-eval parse --dataset [dataset_name] --path [dataset_path]```
from llm_eval import LLM Evaluations
dataset = LLM Evaluations.parse(dataset_name)```
What is the purpose of the LLMEval Dataset Parser?
The LLMEval Dataset Parser simplifies the process of working with LLM benchmark datasets by providing a standardized interface for parsing, validating, and managing datasets.
How do I install the LLMEval Dataset Parser?
You can install it using pip:
pip install llm-eval-parser```
**Can I use the parser with custom or unsupported datasets?**
Yes, the parser supports custom datasets. Contact the developers for guidance on integrating unsupported formats.