{"id":34582367,"url":"https://github.com/experimaestro/experimaestro-ir","last_synced_at":"2025-12-24T10:19:05.135Z","repository":{"id":57427656,"uuid":"220486127","full_name":"experimaestro/experimaestro-ir","owner":"experimaestro","description":"IR module for 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Status](https://readthedocs.org/projects/experimaestro-ir/badge/?version=latest)](https://experimaestro-ir.readthedocs.io/en/latest/?badge=latest)\n[![PyPI version](https://badge.fury.io/py/experimaestro-ir.svg)](https://badge.fury.io/py/experimaestro-ir)\n\n# Information Retrieval for experimaestro\n\nInformation Retrieval module for [experimaestro](https://experimaestro-python.readthedocs.io/)\n\nThe full documentation can be read at [IR@experimaestro](https://experimaestro-ir.readthedocs.io/).\n\nYou can find experiments built on top of XPMIR on the [xpmir github workspace](https://github.com/orgs/xpmir/repositories).\n\nFinally, you can find the [roadmap](https://github.com/experimaestro/experimaestro-ir/issues/9).\n\n## Install\n\nBase experimaestro-IR can be installed with `pip install xpmir`.\nFunctionalities can be added by installing optional dependencies:\n\n- `pip install xpmir[neural]` to install neural-IR packages (torch, etc.)\n- `pip install xpmir[anserini]` to install Anserini related packages\n\nFor the development version, you can:\n\n- If you just want the development version: install with `pip install git+https://github.com/experimaestro/experimaestro-ir.git`\n- If you want to edit the code: clone and then do a `pip install -e .` within the directory\n\n## What's inside?\n\n- Collection management (using datamaestro)\n    - Interface for the [IR datasets library](https://ir-datasets.com/)\n    - Splitting IR datasets\n    - Shuffling training triplets\n- Representation\n    - Word Embeddings\n    - HuggingFace transformers\n- Indices\n    - dense: [FAISS](https://github.com/facebookresearch/faiss) interface\n    - sparse: [xpmir-rust library](https://github.com/experimaestro/experimaestro-ir-rust)\n- Standard Indexing and Retrieval\n    - Anserini\n- Learning to Rank\n    - Pointwise\n    - Pairwise\n    - Distillation\n- Neural IR\n    - Cross-Encoder\n    - Splade\n    - DRMM\n    - ColBERT\n- Paper reproduction:\n    - *MonoBERT* (Passage Re-ranking with BERT. Rodrigo Nogueira and Kyunghyun Cho. 2019)\n    - (alpha) *DuoBERT* (Multi-Stage Document Ranking with BERT. Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, Jimmy Lin. 2019)\n    - (beta) *Splade v2* (SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval, Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. SIGIR 2021)\n    - (planned) ANCE\n- Pre-trained models\n    - [HuggingFace](https://huggingface.co) [integration](https://experimaestro-ir.readthedocs.io/en/latest/pretrained.html) (direct, through the Sentence Transformers library)\n\n## Thanks\n\nSome parts of the code have been adapted from [OpenNIR](https://github.com/Georgetown-IR-Lab/OpenNIR)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fexperimaestro%2Fexperimaestro-ir","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fexperimaestro%2Fexperimaestro-ir","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fexperimaestro%2Fexperimaestro-ir/lists"}