---
source: https://iinventedlight.com/library/notes/hf-datasets-faiss-search.md
title: "Add a FAISS search index to a Hugging Face dataset"
license: CC-BY-4.0
license_url: https://creativecommons.org/licenses/by/4.0/
source_license: "Apache-2.0 (huggingface/datasets docs); restated in our own words"
attribution: "Summary by iinventedlight (AI-assisted). Sources: Hugging Face (Datasets docs), Search index · Hugging Face, Apache-2.0 (huggingface/datasets docs); Hugging Face, Main classes, Apache-2.0 (huggingface/datasets docs)."
author: "iinventedlight (synthesis of cited sources); text drafted with AI assistance"
date: 2026-11-04
status: published
checked_on: 2026-11-05
as_of: 2026-11-05
confidence: medium
untested: "No code was run; only the fetched Hugging Face documentation pages were read."
category: huggingface-datasets
topic_area: "datasets: search"
tags: huggingface, datasets, faiss, embeddings, search
sources:
  - id: S1
    title: "Search index · Hugging Face"
    publisher: Hugging Face (Datasets docs)
    url: https://huggingface.co/docs/datasets/faiss_es
    accessed: 2026-11-05
    license: "Apache-2.0 (huggingface/datasets docs)"
  - id: S2
    title: "Main classes"
    publisher: Hugging Face
    url: https://huggingface.co/docs/datasets/package_reference/main_classes
    accessed: 2026-11-05
    license: "Apache-2.0 (huggingface/datasets docs)"
    license: "Apache-2.0 (huggingface/datasets docs)"
---
# Hugging Face Datasets: FAISS search

## Short answer
Add a FAISS index on an embedding column, then call `get_nearest_examples` or `search` for vector similarity retrieval. [S1][S2]

## Points
- FAISS finds examples by vector similarity. [S1]
- `add_faiss_index` attaches an index you query later. [S2]
- The index name is what `get_nearest_examples` / `search` use. [S2]

## Claims
- id: C1
  claim: FAISS enables searching for examples in a dataset.
  source: S1
  evidence: "FAISS and Elasticsearch enables searching for examples in a dataset"
- id: C2
  claim: FAISS retrieves by vector similarity.
  source: S1
  evidence: "FAISS retrieves documents based on the similarity of their vector representations"
- id: C3
  claim: add_faiss_index builds the index on a column.
  source: S2
  evidence: "add_faiss_index"
- id: C4
  claim: get_nearest_examples uses the named index.
  source: S2
  evidence: "used to call get_nearest_examples() or search()"

## Sources
- [S1] Search index · Hugging Face. Hugging Face (Datasets docs). https://huggingface.co/docs/datasets/faiss_es . License: Apache-2.0 (huggingface/datasets docs). Accessed 2026-11-05.
- [S2] Main classes. Hugging Face. https://huggingface.co/docs/datasets/package_reference/main_classes . License: Apache-2.0 (huggingface/datasets docs). Accessed 2026-11-05.

License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Summary by iinventedlight (AI-assisted).

Source notice: Hugging Face Datasets documentation, Apache License 2.0 (https://github.com/huggingface/datasets/blob/main/LICENSE).