similarity
pgANN
| similarity | pgANN | |
|---|---|---|
| 7 | 2 | |
| 996 | 290 | |
| 0.0% | 0.3% | |
| 6.5 | 0.0 | |
| 29 days ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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similarity
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New free tool that uses fine-tuned BERT model to surface answers from research papers
Tensorflow Ranking and Tensorflow similarity (maybe relevant/irrelevant contrastive learning?) look like they could be useful.
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Non-Machine Learning Image Matching with a Vector DB
There is the metric learning problem to learn a hash for similarity https://github.com/tensorflow/similarity
That said, I don't see many good models available for download on tfhub or huggingface optimized for it, but you can always programmatically modify your images (if you truly mean identical to humans) - change white balance, crop, rotate, select adjacent frames from videos, etc. and optimize a network that is small enough for you to be satisfied and see if that works, as a possible alternative.
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Face Detection for 520 People
Metric learning has great implementations inside Tensorflow Similarity library: https://github.com/tensorflow/similarity Although the documentation is quite bad, but the jupyter notebooks are great.
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[P] TensorFlow Similarity 0.16 is out
Just a quick note that TensorFlow Similarity 0.16 is out -- this release beside adding the XMB loss is mostly focus on refactoring and optimizing the core components to ensure everything works smoothly and accurately. Details are in the changelog as usual and a simple pip install -U tensorflow_similarity should just work.
- Self-supervised learning added to TensorFlow Similarity
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[P] TensorFlow Similarity now self-supervised training
Very happy to announce that as part of the 0.15 release, TensorFlow Similarity now support self-supervised learning using STOA algorithms. To help you get started we included in the release a detailed getting started notebook that you can run in Colab. This notebook shows you how to use SimSiam self-supervised pre-training to almost double the accuracy compared to a model trained from scratch on CIFAR 10.
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TensorFlow Introduces ‘TensorFlow Similarity’, An Easy And Fast Python Package To Train Similarity Models Using TensorFlow
Github: https://github.com/tensorflow/similarity
pgANN
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Pinecone raises $100M Series B
Why do you use pgvector instead of pgANN? My understanding is pgANN is built with FAISS. When I compared pgvector with FAISS, pgvector was 3-5x slower.
https://github.com/netrasys/pgANN
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Pgvector – vector similarity search for Postgres
Love it! Need better ANNs approaches in databases, using external servers such as Milvus, faiss is a pita
related: https://github.com/netrasys/pgANN
What are some alternatives?
pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
ann-benchmarks - Benchmarks of approximate nearest neighbor libraries in Python
quaterion - Blazing fast framework for fine-tuning similarity learning models
smlar - PostgreSQL extension for an effective similarity search || mirror of git://sigaev.ru/smlar.git || see https://www.pgcon.org/2012/schedule/track/Hacking/443.en.html
ContraD - Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)
Milvus - A cloud-native vector database, storage for next generation AI applications
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
faiss - A library for efficient similarity search and clustering of dense vectors.
sparse_dot_topn - Python package to accelerate the sparse matrix multiplication and top-n similarity selection
DiskANN - Graph-structured Indices for Scalable, Fast, Fresh and Filtered Approximate Nearest Neighbor Search
Keras - Deep Learning for humans
citrus - (distributed) vector database