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Dev tools · alternatives · 2026

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24 alternatives to Implementation of Poincaré Embeddings(Facebook Research) in Numpy

The implementation is at: https://github.com/nishnik/poincare_embeddings Corresponding blog post: https://medium.com/towards-data-science/facebook-research-ju... Corresponding paper: https://arxiv.org/abs/1705.08039 This paper explores Poincare disk model instead of Euclidean space for embedding hierarchical data

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier. Implementation of Poincaré Embeddings(Facebook Research) in Numpy launched in 2017; newer entries below may have overtaken it.

  1. 1

    An open, lightweight multimodal embedding model

    17d ago · blog.google · its alternatives →

  2. 2

    End-to-end deep dive of the project, spanning a large GPU cluster, distributed RocksDB, and terabytes of sharded HNSW.

    2025 · blog.wilsonl.in · its alternatives →

  3. 3

    I've been playing with embeddings and wanted to try out what results the embedding layer will produce based on just word-by-word input and addition / subtraction, beyond what many videos / papers mention (like the obvious king-man+woman=queen). So I built something that doesn't just give the first answer, but ranks the matches based on distance / cosine symmetry. I polished it a bit so that others can try it out, too. For now, I only have nouns (and some proper nouns) in the dataset, and pick the most common interpretation among the homographs. Also, it's case sensitive.

    2025 · calc.datova.ai · its alternatives →

  4. 4IC

    Hi! This is an infinite canvas note-taking tool where notes are laid out in a non-Euclidean, hyperbolic geometric space. As you drag and navigate through the view, you’ll experience a unique fluid distortion that naturally leverages your brain's spatial memory. I’ve been obsessed with the concept of space in HCI for years. Many modern UI patterns are essentially workarounds for the lack of screen real estate. While researching zoom-based UIs a while back, I stumbled upon old HCI papers that used the Poincaré disk model of the hyperbolic plane to organize data. It elegantly projects an…

    Jun 2026 · uonr.github.io · its alternatives →

  5. 5IM

    As a grad student (and an ADHDer), I had trouble doing literature review systematically. To combat this, I made a website that finds similar papers using the meaning of the thing I am looking for. I used MixedBread's [^1] embedding model to generate vectors from the abstracts. I store and search similar vectors using Milvus [^2] and finally use Gradio [^3] to serve the frontend. I update the vector database weekly by pulling the metadata dataset from Kaggle [^4]. To speed up the search process on my free oracle instance, I binarise the embeddings and use Hamming distance as a metric. I would…

    2024 · papermatch.mitanshu.tech · its alternatives →

  6. 6

    Hey HN, we're happy to release Mycelium, a JavaScript library for creating graph visualizations of machine learning models or any other directed acyclic graphs. Mycelium powers the graph viewer of the Talaria [0] a research model visualization and optimization system, which was used to optimize the efficiency of Apple Foundation Models [1]. Everything works entirely on the client-side in the browser — we provide a rudimentary ONNX loader out of the box, which you can try by dragging model files into our website. It is also simple to define loaders for your own model formats. The library was…

    2025 · apple.github.io · its alternatives →

  7. 7MD
  8. 8ED

    I compared iTerm2 and Neovim color themes by extracting their palettes from theme files and computing a similarity score. Theme pairings are recommended for users who want a consistent look across their terminal and editor, since their palettes are perceptually similar according to CIELAB-based distance metrics.

    2018 · rpubs.com · its alternatives →

  9. 9PA

    Hey everyone, I was wondering if a Poincaré disk would be able to usefully show the local structure of a graph while showing most of one I used a collection of ML papers to explore this

    Mar 2026 · paperverse.net · its alternatives →

  10. 10

    An open-source database for machine learning

    2021 · github.com · its alternatives →

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    Creating high-quality scientific figures can be time-consuming and challenging, even though sketching ideas on paper is relatively easy. Furthermore, recreating existing figures that are not stored in formats preserving semantic information is equally complex. To tackle this problem, we introduce DeTikZify, a novel multimodal language model that automatically synthesizes scientific figures as semantics-preserving TikZ graphics programs based on sketches and existing figures. We also introduce a Monte Carlo Tree Search-based inference algorithm that enables DeTikZify to iteratively refine its…

    2024 · github.com · its alternatives →

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    The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform

    2021 · github.com · its alternatives →

  13. 13

    Here's a small demonstration of the fundamental aspects of the word-to-vec algorithm. It's implemented in a single python script and depends only on a single text file for training. It's not meant to be blazingly fast or anything, just a toy example to aid my understanding of how word vectors might be learnt from a corpus.

    2023 · github.com · its alternatives →

  14. 14NN

    Hi HN. Peter here. As a machine learning engineer, I mostly think in terms of feature vectors, embeddings, and matrices. One of the most useful byproducts of deep neural networks is embeddings because they allow us to represent high-dimensional data in terms of lower-dimensional latent vectors. These feature vectors can be used for downstream applications like similarly search, recommendation systems and near duplicate detection. As an ML engineer, I was frustrated by the lack of a datastore in which vectors are first-class citizens. As a result, most ML engineers, including myself, end up…

    2021 · its alternatives →

  15. 15

    We’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…

    2024 · github.com · its alternatives →

  16. 16

    Heirarchical Navigable Small Worlds. Contribute to dicroce/hnsw development by creating an account on GitHub.

    2025 · github.com · its alternatives →

  17. 17

    Hello everyone! I've been working on this project for a few months as part of my thesis in Machine Learning. It's meant to be a library that provides an easy-to-use but flexible API to design and train Diffusion Models. I decided to make it because I wanted to quickly prototype a Diffusion Model but there were no good tools to do it with. I think it really can help people prototype their own Diffusion Models a lot faster and only in a few lines of code. The base idea is to have a Model class that takes different modules corresponding to the different aspects of the Diffusion Model process…

    2023 · github.com · its alternatives →

  18. 18IM

    Just a fun toy I wanted to make. I've been studying and playing around with language models lately and have always been intrigued by how words are processed by these models. Since the vectors generated by embedding models is in very high dimensional space, I thought it would be cool to reduce them to 3D vectors and visualise them myself. This is what I have so far!

    2023 · seesaurus.com · its alternatives →

  19. 19

    We connect visual data to AI applications.

    2024 · quasara.io · its alternatives →

  20. 20PF

    Introducing embeds.ai: an embedding playground to compare how embedding models work on a real world use case (retrieval augmented generation for Wikipedia articles + Elad Gil's High growth handbook) A few weeks ago, Shreyan and I were looking for an embedding model to use for RAG. We eventually came across the MTEB leaderboard, but we struggled to understand the benchmark scores. We wanted a tool to test various embedding models with example queries on real-world datasets. After unsuccessfully looking for such a “playground”, we decided to just build one ourselves! We embedded HuggingFace’s…

    2023 · embeds.ai · its alternatives →

  21. 213W
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    We open-sourced catsu, a Python client for embedding APIs. The problem: every embedding provider has a different SDK with different bugs. OpenAI has undocumented token limits. VoyageAI's retry logic was broken until September. Cohere breaks downstream libraries every release. LiteLLM's embedding support is minimal. catsu provides: - One API for 11 providers (OpenAI, Voyage, Cohere, Jina, Mistral, Gemini, etc.) - Bundled database of 50+ models with pricing, dimensions, and benchmark scores - Built-in retry with exponential backoff - Automatic cost tracking per request - Full async support…

    Dec 2025 · catsu.dev · its alternatives →

  23. 23MA

    2017 · lmcinnes.github.io · its alternatives →

  24. 24

    An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019). - benedekrozemberczki/MixHop-and-N-GCN

    2019 · github.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →