| tags: | |
| - giskard | |
| - knowledge-base | |
| - information-retrieval | |
| task_categories: | |
| - text-generation | |
| - text2text-generation | |
| - question-answering | |
| - text-retrieval | |
| # Dataset Card for GTimothee/my-knowledge-base | |
| > This repository was created using the [giskard](https://github.com/Giskard-AI/giskard) library, an open-source Python framework designed to evaluate and test AI systems. | |
| This dataset comprises a giskard's `KnowledgeBase` containing 310 documents. If embeddings were generated before the saving process, they are included and will be automatically loaded into a vector store when required. | |
| ## Usage | |
| You can load this knowledge base using the following code: | |
| ```python | |
| from giskard.rag import KnowledgeBase | |
| kb = KnowledgeBase.load_from_hf_hub("GTimothee/my-knowledge-base") | |
| ``` | |
| ## Configuration | |
| The configuration details for this Knowledge Base (can also be found in the `config.json` file): | |
| ```bash | |
| { | |
| "columns": null, | |
| "chunk_size": 2048, | |
| "min_topic_size": 8, | |
| "language": "en", | |
| "seed": null, | |
| "embedding_model": null | |
| } | |
| ``` | |
| --- | |
| <h2 style="text-align: center;"> | |
| <span style="display: inline-flex; align-items: center;"> | |
| Built with | |
| <a href="https://giskard.ai" target="_blank" style="display: inline-flex;"> | |
| <img src="https://cdn.prod.website-files.com/601d6f7d0b9c984f07bf10bc/62983fa8ef716259c397a57d_logo.svg" | |
| alt="Giskard Logo" | |
| width="100"> | |
| </a> | |
| </span> | |
| </h2> | |
| <div style="text-align: center;"> | |
| <a href="https://github.com/Giskard-AI/giskard" target="_blank" style="display: inline-flex;"> Giskard </a> helps identify performance, bias, and security issues in AI applications, supporting both LLM-based systems like RAG agents and traditional machine learning models for tabular data. | |
| </div> |