README.md

---
language: en
library_name: bm25s
tags:
- bm25
- bm25s
- retrieval
- search
- lexical
---

# BM25S Index

This is a BM25S index created with the [`bm25s` library](https://github.com/xhluca/bm25s) (version `0.1.7`), an ultra-fast implementation of BM25. It can be used for lexical retrieval tasks.

💻[BM25S GitHub Repository](https://github.com/xhluca/bm25s)\
🌐[BM25S Homepage](https://bm25s.github.io)

## Installation

You can install the `bm25s` library with `pip`:

```bash
pip install "bm25s==0.1.7"

# Include extra dependencies like stemmer
pip install "bm25s[full]==0.1.7"

# For huggingface hub usage
pip install huggingface_hub
```

## Loading a `bm25s` index

You can use this index for information retrieval tasks. Here is an example:

```python
import bm25s
from bm25s.hf import BM25HF

# Load the index
retriever = BM25HF.load_from_hub("mteb/index_stackexchange_bm25")

# You can retrieve now
query = "a cat is a feline"
results = retriever.retrieve(bm25s.tokenize(query), k=3)
```

## Saving a `bm25s` index

You can save a `bm25s` index to the Hugging Face Hub. Here is an example:

```python
import bm25s
from bm25s.hf import BM25HF

corpus = [
    "a cat is a feline and likes to purr",
    "a dog is the human's best friend and loves to play",
    "a bird is a beautiful animal that can fly",
    "a fish is a creature that lives in water and swims",
]

retriever = BM25HF(corpus=corpus)
retriever.index(bm25s.tokenize(corpus))

token = None  # You can get a token from the Hugging Face website
retriever.save_to_hub("mteb/index_stackexchange_bm25", token=token)
```

## Advanced usage

You can leverage more advanced features of the BM25S library during `load_from_hub`:

```python
# Load corpus and index in memory-map (mmap=True) to reduce memory
retriever = BM25HF.load_from_hub("mteb/index_stackexchange_bm25", load_corpus=True, mmap=True)

# Load a different branch/revision
retriever = BM25HF.load_from_hub("mteb/index_stackexchange_bm25", revision="main")

# Change directory where the local files should be downloaded
retriever = BM25HF.load_from_hub("mteb/index_stackexchange_bm25", local_dir="/path/to/dir")

# Load private repositories with a token:
retriever = BM25HF.load_from_hub("mteb/index_stackexchange_bm25", token=token)
```

## Stats

This dataset was created using the following data:

| Statistic | Value |
| --- | --- |
| Number of documents | 2161851 |
| Number of tokens | 131389247 |
| Average tokens per document | 60.78 |

## Parameters

The index was created with the following parameters:

| Parameter | Value |
| --- | --- |
| k1 | `1.5` |
| b | `0.75` |
| delta | `0.5` |
| method | `lucene` |
| idf method | `lucene` |