elixir-nx

bumblebee

Elixir2022–2025

elixir-nx / bumblebee

bumblebee

Pre-trained Neural Network models in Axon (+ 🤗 Models integration)

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REPOSITORY AT A GLANCE

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What it is

Pre-trained Neural Network models in Axon (+ 🤗 Models integration)

GitHub

Where it is used

No documented product use has been verified yet.

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Also in these discussions

elixir-explorer/explorer · linked in 2 of the same discussions
elixir-nx/axon · linked in 2 of the same discussions
elixir-nx/nx · linked in 2 of the same discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 5:03:38 AM UTC.

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HN mentions by year12 dated mentions

Observed mentions: 2022-12-16 15:57:49 UTC to 2025-08-06 13:30:16 UTC.

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Submissions	Comments
2022	2022-01-01 00:00:00 UTC	2023-01-01 00:00:00 UTC	1	0	1
2023	2023-01-01 00:00:00 UTC	2024-01-01 00:00:00 UTC	4	0	4
2024	2024-01-01 00:00:00 UTC	2025-01-01 00:00:00 UTC	4	0	4
2025	2025-01-01 00:00:00 UTC	2026-01-01 00:00:00 UTC	3	1	2

What Hacker News says

4 sources

aayushmau5·Aug 7, 2023

Apart from running code inside a "markdown" file, livebook can do much more. You have Smart cells to show charts, run sql queries against a db, run Neural Network tasks such as Image-To-Text generation using Bumblebee[1], etc. It is collaborative as well. [1] https://github.com/elixir-nx/bumblebee

In Elixir Livebook is a secret weapon for documentation

thibaut_barrere·Jul 19, 2023

Elixir is an increasingly interesting platform for ML (see Nx, Axon, and more recently BumbleBee https://github.com/elixir-nx/bumblebee). I'm pretty happy to see this book released in beta.

In “Machine Learning in Elixir” (Beta Book)

josevalim·Apr 14, 2023

José from the Livebook team. I don't think I can make a pitch because I have limited Python/R experience to use as reference. My suggestion is for you to give it a try for a day or two and see what you think. I am pretty sure you will find weak spots and I would be very happy to hear any feedback you may have. You can find my email on my GitHub profile (same username). In general we have grown a lot since the Numerical Elixir effort started two years ago. Here are the main building blocks: * Nx (https://github.com/elixir-nx/nx/tree/main/nx#readme): equivalent to Numpy, deeply inspired by JAX. Runs on both CPU and GPU via Google XLA (also used by JAX/Tensorflow) and supports tensor serving out of the box * Axon (https://github.com/elixir-nx/axon): Nx-powered neural networks * Bumblebee (https://github.com/elixir-nx/bumblebee): Equivalent t

Read the rest

o HuggingFace Transformers. We have implemented several models and that's what powers the Machine Learning integration in Livebook (see the announcement for more info: https://news.livebook.dev/announcing-bumblebee-gpt2-stable-d...) * Explorer (https://github.com/elixir-nx/explorer): Series and DataFrames, as per this thread. * Scholar (https://github.com/elixir-nx/scholar): Nx-based traditional Machine Learning. This one is the most recent effort of them all. We are treading the same path as scikit-learn but quite early on. However, because we are built on Nx, everything is derivable, GPU-ready, distributable, etc. Regarding visualization, we have "smart cells" for VegaLite and MapLibre, similar to how we did "Data Transformations" in the video above. They help you get started with your visualizations and you can jump deep into the code if necessary. I hope this helps!

In Data wrangling in Elixir with Explorer, the power of Rust, the elegance of R

josevalim·Apr 11, 2023

The current pipeline expects PCM audio blobs and, if data is coming from a microphone in the browser, you can do the initial processing and conversion in the browser (see the JS in this single file Phoenix app speech to text example [0]). On the other hand, if you expect a variety of formats (mp3, wav, etc), then shelling out or embedding ffmpeg is probably the quickest path to achieve something. The Membrane Framework[1] is an option here too which includes streaming. I believe Lars is going to do a cool demo with Membrane and ML at ElixirConf EU next week. [0]: https://github.com/elixir-nx/bumblebee/blob/main/examples/ph... [1]: https://membrane.stream/

In Distributed Machine Learning Notebooks with Elixir and Livebook