similarity VS awesome-semantic-search

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

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similarity awesome-semantic-search
7 3
1,013 337
0.4% -
5.9 5.7
6 months ago 11 months ago
Python
Apache License 2.0 Creative Commons Zero v1.0 Universal
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.

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.

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.

What are some alternatives?

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

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.

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

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

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

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

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

haystack - :mag: AI 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.

finetuner - :dart: Task-oriented embedding tuning for BERT, CLIP, etc.

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

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