Num2vec – Numerical Embeddings via Deep Nested RNNs
Num2vec – Numerical Embeddings via Deep Nested RNNs launched on February 1, 2018 with 6 votes, #1,157 of 2,634 launches that month and more than 50% of that year's launches. The site was not reachable when checked in September 2026.
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Neural Networks and Deep Learning2015 · neuralnetworksanddeeplearning.com · ▲95Core concepts behind neural networks and deep learning
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Model2vec – Lightning-fast Static Embeddings for RAG/Semantic Search2024 · github.com · ▲28We’ve recently open-sourced Model2vec, a method to distill sentence transformers into static embeddings that outperform all previous approaches by a large margin on MTEB. Our new models set a new state-of-the-art for static embeddings. Main features: - Our best model (potion-base-8M) has only 8M parameters, which is ~30mb on disk - Inference is ~500x faster than the distilled base model (bge-base), on a CPU - New models can be distilled in 30 seconds on a CPU without requiring a dataset - just a vocabulary - Numpy-only inference: The packaged can be install the package with minimal…
KANN – mid-scale deep learning and autodiff in ANSI C (4 files; 4k LOC)2018 · github.com · ▲5A lightweight C library for artificial neural networks - attractivechaos/kann
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