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release v0.5.1
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bclavie committed Aug 16, 2024
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1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -14,6 +14,7 @@ Welcome to `rerankers`! Our goal is to provide users with a simple API to use an

## Updates

- v0.5.1: Minor change making RankedResults subscribable, meaning results[0] will return the first result, etc...
- v0.5.0: Added support for the current state-of-the-art rerankers, BAAI's series of `BGE` layerwise LLM rerankers, based on [Gemma](https://huggingface.co/BAAI/bge-reranker-v2.5-gemma2-lightweight) and MiniCPM. These are different from RankGPT, as they're not listwise: the models are repurposed as "cross-encoders", and do output logit scores.
- v0.4.0: ColBERT performance improvement! It should now be faster and result in stronger results following implementation of the JaColBERTv2.5 dynamic query length method. This version also now supports HuggingFace's Text-Embedding-Server (TEI) inference as an API reranker option, thanks to [@srisudarsan](https://github.com/srisudarsan).
- v0.3.1: T5 bugfix and native default support for new Portuguese T5 rerankers.
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2 changes: 1 addition & 1 deletion pyproject.toml
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Expand Up @@ -14,7 +14,7 @@ packages = [
name = "rerankers"


version = "0.5.0"
version = "0.5.1"

description = "A unified API for various document re-ranking models."

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2 changes: 1 addition & 1 deletion rerankers/__init__.py
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from rerankers.documents import Document

__all__ = ["Reranker", "Document"]
__version__ = "0.5.0"
__version__ = "0.5.1"

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