---
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
}
```

---

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  <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.
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