Muennighoff
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Update BM25S model
Browse files- .gitattributes +3 -0
- README.md +109 -0
- corpus.jsonl +3 -0
- corpus.mmindex.json +3 -0
- data.csc.index.npy +3 -0
- indices.csc.index.npy +3 -0
- indptr.csc.index.npy +3 -0
- params.index.json +11 -0
- vocab.index.json +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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corpus.jsonl filter=lfs diff=lfs merge=lfs -text
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corpus.mmindex.json filter=lfs diff=lfs merge=lfs -text
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vocab.index.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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language: en
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library_name: bm25s
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tags:
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- bm25
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- bm25s
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- retrieval
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- search
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- lexical
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---
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# BM25S Index
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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.
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💻[BM25S GitHub Repository](https://github.com/xhluca/bm25s)\
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🌐[BM25S Homepage](https://bm25s.github.io)
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## Installation
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You can install the `bm25s` library with `pip`:
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```bash
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pip install "bm25s==0.1.7"
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# Include extra dependencies like stemmer
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pip install "bm25s[full]==0.1.7"
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# For huggingface hub usage
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pip install huggingface_hub
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```
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## Loading a `bm25s` index
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You can use this index for information retrieval tasks. Here is an example:
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```python
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import bm25s
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from bm25s.hf import BM25HF
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# Load the index
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retriever = BM25HF.load_from_hub("mteb/index_wikipedia_bm25")
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# You can retrieve now
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query = "a cat is a feline"
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results = retriever.retrieve(bm25s.tokenize(query), k=3)
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```
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## Saving a `bm25s` index
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You can save a `bm25s` index to the Hugging Face Hub. Here is an example:
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```python
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import bm25s
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from bm25s.hf import BM25HF
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corpus = [
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"a cat is a feline and likes to purr",
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"a dog is the human's best friend and loves to play",
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"a bird is a beautiful animal that can fly",
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"a fish is a creature that lives in water and swims",
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]
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retriever = BM25HF(corpus=corpus)
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retriever.index(bm25s.tokenize(corpus))
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token = None # You can get a token from the Hugging Face website
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retriever.save_to_hub("mteb/index_wikipedia_bm25", token=token)
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```
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## Advanced usage
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You can leverage more advanced features of the BM25S library during `load_from_hub`:
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```python
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# Load corpus and index in memory-map (mmap=True) to reduce memory
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retriever = BM25HF.load_from_hub("mteb/index_wikipedia_bm25", load_corpus=True, mmap=True)
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# Load a different branch/revision
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retriever = BM25HF.load_from_hub("mteb/index_wikipedia_bm25", revision="main")
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# Change directory where the local files should be downloaded
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retriever = BM25HF.load_from_hub("mteb/index_wikipedia_bm25", local_dir="/path/to/dir")
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# Load private repositories with a token:
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retriever = BM25HF.load_from_hub("mteb/index_wikipedia_bm25", token=token)
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```
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## Stats
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This dataset was created using the following data:
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| Statistic | Value |
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| --- | --- |
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| Number of documents | 3811232 |
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| Number of tokens | 438712919 |
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| Average tokens per document | 115.11 |
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## Parameters
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The index was created with the following parameters:
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| Parameter | Value |
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| --- | --- |
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| k1 | `1.5` |
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| b | `0.75` |
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| delta | `0.5` |
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| method | `lucene` |
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| idf method | `lucene` |
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corpus.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:e8229a18852e6b6b4b241ade62a8181d7811ddf1b281e25221e84b3dd0b0bf65
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size 5821785533
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corpus.mmindex.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:1ad6f8bb6791d785aae732482a33606bcff7981014fbc677b89657d9a1cd080a
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size 41197814
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data.csc.index.npy
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version https://git-lfs.github.com/spec/v1
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oid sha256:9a18b3c07afb8a58d8df6c75b6d7ad5317d149308678990338b3d6b64141d46b
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size 1754851804
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indices.csc.index.npy
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version https://git-lfs.github.com/spec/v1
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oid sha256:7cc32419d7697092dfacdae5a3ce9e2bbd79b5f2f614e9386a0624c3dc01087f
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size 1754851804
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indptr.csc.index.npy
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version https://git-lfs.github.com/spec/v1
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oid sha256:6056ce965ef854c72c83744cd3aaab3a390b9b32f111683b15b86a2dd55eccf8
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size 11434096
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params.index.json
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{
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"k1": 1.5,
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"b": 0.75,
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"delta": 0.5,
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"method": "lucene",
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"idf_method": "lucene",
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"dtype": "float32",
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"int_dtype": "int32",
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"num_docs": 3811232,
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"version": "0.1.7"
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}
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vocab.index.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:75de8daadb78bb341b1de32deae3cfb101f5417c75087e6cbe9a39f66769ef65
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size 56953104
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