mamba | rye | |
---|---|---|
15 | 31 | |
9,506 | 11,368 | |
15.3% | 3.9% | |
8.1 | 9.7 | |
9 days ago | 7 days ago | |
Python | Rust | |
Apache License 2.0 | MIT License |
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.
mamba
-
Based: Simple linear attention language models
> how the recall can grow unbounded with no tradeoff
this? https://github.com/state-spaces/mamba/issues/175
-
Mamba: The Easy Way
If you want to learn this stuff as a computer engineer, you can read the code here [0]. I find the math quite helpful.
[0]: https://github.com/state-spaces/mamba
- FLaNK Stack 05 Feb 2024
- Introduction to State Space Models (SSM)
-
Fortran inference code for the Mamba state space language model
This model was discussed recently: https://news.ycombinator.com/item?id=38522428 It's a new kind of ML model architecture that can be used instead of a transformer in LLMs.
See also the original repo from the paper: https://github.com/state-spaces/mamba
-
Mamba outperforms transformers "everywhere we tried"
[2] - https://github.com/state-spaces/mamba
Out of curiosity, does anyone feel as though there's any benefit to linking to reddit when we can link to whatever the link is? I for one do not click the link and read discussion on reddit - if I wanted that sort of discussion, I would browse there, not HN.
- GitHub – State-Spaces/Mamba
-
Generate valid JSON with Mamba models
The library is compatible with any auto-regressive model, not transformers. To prove our point we integrated Mamba, a new state-space model architecture, to the library. Try it out!
-
[D] Thoughts on Mamba?
I ran the NanoGPT of Karparthy replacing Self-Attention with Mamba on his TinyShakespeare Dataset and within 5 minutes it started spitting out the following:
-
Mamba-Chat: A Chat LLM based on State Space Models
You might have come across the paper Mamba paper in the last days, which was the first attempt at scaling up state space models to 2.8B parameters to work on language data.
rye
-
Trying Out Rye
I tried out rye + uv on a recent greenfield project. They are awesome tools and I'm really excited about their potential.
For me, rye (+ uv underneath) has perhaps the perfect workflow for an open source Python project. So I'm definitely using rye for that from now in -- instead of, say, poetry -- or hatchling directly, following the PyPA boilerplate[1].
You have a way of doing local development against any Python interpreter version. You have a way of tweaking dependencies. It all works atop "standard" PyPA infrastructure like pyproject.toml. You have a single command to build[1] project artifacts, like wheels. And you have a single command to publish new artifact versions to PyPI[2].
I think if you're doing local development on a project that is not meant to be published to PyPI, like a private Django project, then whether to use rye becomes more of a debate. For example, for a Django project I'm working on, I decided to just use uv directly, along with a Makefile. This is because during development of a Django project, I preferred to just use a plain requirements.txt (really, requirements.in) file, avoid the sync/lock workflow that rye imposes, and avoid the need to use something like rye run. And rye's ability to package didn't solve a problem since the Django project wasn't being deployed via a PyPA packaging mechanism.
But this is probably also because the Python interpreter/venv management problem, for me, is already handled by pyenv. I think if you're not already a pyenv user, rye is even more appealing because it handles "all" of the Python issues -- interpreters, requirements/dependencies, and packaging/publishing. (As well as a number of other standard issues besides, like testing, linting, and formatting.) But, in my case, I could hand venv management to uv, and then make dependency management part of a larger Makefile for my Django project, including custom linting, testing, and deployment steps. I wrote a little bit about my high level thoughts on Python packaging and dependency management, though this post was written before rye and uv were out.[4]
I'll also say, I found a little bug in how rye (+ hatch) interacted with my local git setup, and reported it to the rye team, and they helped me get to the bottom of it rather quickly.[5]
[1]: https://packaging.python.org/en/latest/tutorials/packaging-p...
[2]: https://rye-up.com/guide/commands/build/
[3]: https://rye-up.com/guide/commands/publish/
[4]: https://amontalenti.com/2022/10/09/python-packaging-and-zig
[5]: https://github.com/astral-sh/rye/issues/793
-
Pyenv – lets you easily switch between multiple versions of Python
I've been using Rye[0] lately, which has been pretty good. It's really just a wrapper around a bunch of underlying tools - it's nice to not have to worry about those and let Rye do it's thing.
All that being said, the creator of Rye is 100% cognizant of that XKCD comic, this [1] is a nice read.
I'm not super well versed in Python tooling at all. I've had to work a lot in Python in the past 6+ months, and I become super confused when I tried making a Python project in my spare time.
I settled on Rye because it just seemed to be the easiest to use.
[0]: https://rye-up.com/
-
Uv: Python Packaging in Rust
I think Rye actually does handle this mostly correctly (as the sibling comment said). I got through some of it here: https://github.com/mitsuhiko/rye/issues/671. I think actually it's very close to what I actually want (maybe not what Armin wants with multiversion).
-
RustPython
Rye[1] is an all in one manager for python projects. Including the python versions and virtualenv, pip etc etc... It seperates tool deps from app deps. Its all configured through a pyproject.toml config file.
Its still new but works well. I'm transiting to it from an unholy mess of pyenv, pip installs and other manual hacks.
If you're starting a new python project that is more than just a straightforward script I'd use Rye from the get go.
[1]https://rye-up.com/
- FLaNK Stack 05 Feb 2024
-
Rye: A Vision Continued
Your first comment irked me because it adds zero value to the discussion. You lazily threw out XKCD 927 which the Rye author explicitly mentioned themselves.
If you click into their link "Should Rye Exist" [1] you'll see that XKCD 927 is literally the first sentence and full width image.
[1] https://github.com/mitsuhiko/rye/discussions/6
-
iJustWantAStableExperience
Try Rye.
-
Poetry: Python Packaging and Dependency Management
Since this is a discussion on dependency management in Python - does anyone use rye [0] regularly now? I'm interested in using it but want a little more social validation before I try - some issues with package managers only appear after you've invested considerable time.
[0]: https://rye-up.com/
-
Why not tell people to “simply” use pyenv, poetry or anaconda
The short term solution is "relieving the packaging pain" link in the article.
The long term solution is described in the "What a solution could look like?" section of https://www.bitecode.dev/p/why-is-the-python-installation-pr...
The community is buzzing with attempts to fix those issues this year, so I’m hopping those posts will become obsolete one day.
Flask’s author is attempting something interesting with rye: https://github.com/mitsuhiko/rye
Trio’s author is drafting a spec for the equivalent of wheels, but for the whole python interpreter: https://github.com/njsmith/posy/blob/main/pybi/README.md
Not advocating to use them right now, but the fact is bootstrapping Python is finally acknowledged as one major cause of packaging issues and a priority to solve.
-
Show /r/rust: self-replace, a create to self-delete and self-replace binaries on Mac, Linux and Windows
I'm building a package manager for Python (Rye) in Rust and it is modeled after cargo and rustup. It like rustup manages itself. This means it has commands such as rye self update which downloads the latest version and swaps itself out. Likewise there is rye self uninstall which uninstalls rye itself.
What are some alternatives?
miniforge - A conda-forge distribution.
uv - An extremely fast Python package installer and resolver, written in Rust.
pip - The Python package installer
huak - My experimental python package manager.
llm.f90 - LLM inference in Fortran
mise - dev tools, env vars, task runner
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
mamba-how-to - Using Mamba-forge for Python environment management
mamba-chat - Mamba-Chat: A chat LLM based on the state-space model architecture 🐍
poetry-plugin-export - Poetry plugin to export the dependencies to various formats
spack - A flexible package manager that supports multiple versions, configurations, platforms, and compilers.
zpy - Zsh helpers for Python venvs, with uv or pip-tools