Recent Releases of cherche
cherche - 2.1.0
Cherche 2.1.0 is available, it's been a long time without updates 🥳
- Updated default TfIdf retriever with vectorizer from LeNLP which is written in Rust and much faster.
- Added BM25 retriever using LeNLP BM25Vectorizer with is written in Rust and very fast.
- Python
Published by raphaelsty over 1 year ago
cherche - 2.0.0
Excited to announce the release of Cherche 2.0, a comprehensive open-source search engine toolkit for Python. This new version comes with a host of new features and improvements, including:
- Batch-computation
- Optimization
- Progress bars
- Cross-Encoders compatibility
- Focus on retrievers, rankers and indexes compatible with Python.
- Requirements are lighter modular
- Python
Published by raphaelsty almost 3 years ago
cherche - 1.0.0
What's Changed
Here is an essential update for Cherche! 🥳
- Added compatibility with two new open-source retrievers: Meilisearch and TypeSense.
- Compatibility with the Milvus index to use the
retriever.Encoderandretriever.DPRmodels on massive corpora. - Compatibility with the Milvus index to store ranker embeddings in a database rather than in memory.
- Progress bar when pre-computing embeddings by Encoder, DPR retrievers and Encoder, DPR rankers.
- The path parameter is no longer used.
- All pipelines (voting, intersection, concatenation) produce a similarity score. To do so, the pipeline object applies a softmax to normalize the scores, thus allowing us to "compare" the scores of two distinct models.
- Integration of collaborative filtering models via adding a Recommend retriever and a Recommend ranker (indexation via Faiss and compatible with Milvus) to consider users' preferences in the search.
Cherche is now fully compatible with large-scale corpora and deeply integrates collaborative filtering. Updates retains the previous API and is compatible with previous versions.
- Python
Published by raphaelsty over 3 years ago
cherche - 0.1.0
Added compatibility with the ONNX environment and quantization to significantly speed up sentence transformers and question answering models. 🏎
It is now possible to choose the type of index for the Encoder and DPR retrievers in order to process the largest corpora while using the GPU.
- Python
Published by raphaelsty over 3 years ago
cherche - 0.0.4
Update of the encoder retriever and the DPR retriever. Documents in the Faiss index will not be duplicated. Query embeddings can now be pre-computed for ranker Encoder and ranker DPR to speed up evaluation without having to compute it again.
- Python
Published by raphaelsty about 4 years ago