awesome-semantic-search VS similarity

Compare awesome-semantic-search vs similarity and see what are their differences.

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awesome-semantic-search similarity
3 7
320 996
- 0.2%
5.7 6.5
5 months ago about 1 month ago
Python
Creative Commons Zero v1.0 Universal Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-semantic-search

Posts with mentions or reviews of awesome-semantic-search. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

similarity

Posts with mentions or reviews of similarity. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

What are some alternatives?

When comparing awesome-semantic-search and similarity you can also consider the following projects:

Milvus - A cloud-native vector database, storage for next generation AI applications

pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

contract-discovery - Data and additional information regarding the paper: Contract Discovery. Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines (to appear in Findings of EMNLP).

pgANN - Fast Approximate Nearest Neighbor (ANN) searches with a PostgreSQL database.

elasticsearch-learning-to-rank - Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch

quaterion - Blazing fast framework for fine-tuning similarity learning models

ColBERT - ColBERT: state-of-the-art neural search (SIGIR'20, TACL'21, NeurIPS'21, NAACL'22, CIKM'22, ACL'23, EMNLP'23)

ContraD - Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)

haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time

sparse_dot_topn - Python package to accelerate the sparse matrix multiplication and top-n similarity selection

Keras - Deep Learning for humans