pyre-check
mamba
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pyre-check | mamba | |
---|---|---|
24 | 15 | |
6,673 | 9,074 | |
0.5% | 25.0% | |
9.9 | 8.3 | |
7 days ago | 24 days ago | |
OCaml | Python | |
MIT License | Apache License 2.0 |
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.
pyre-check
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Pylyzer – A fast static code analyzer and language server for Python
Did you come across pyre in your search? MIT license and pretty fast.
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Enhance Your Project Quality with These Top Python Libraries
Pyre is a performant type-checker developed by Facebook. Pyre can analyse codebases with millions of lines of code incrementally – providing instantaneous feedback to developers as they write code.
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
Pyre from Meta, pyright from Microsoft and PyType from Google provide additional assistance. They can 'infer' types based on code flow and existing types within the code.
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Ruff v0.1.0
Have you seen Pyre[0]? Not Rust, OCaml, and pretty fast. Made by a team at Meta and open sourced on GitHub. If you use python-lsp, I wrote an extension[1] to enable integration (though I haven't tested it recently, been programming in rust; it is mostly a "for me" extension).
- Should I Rust or should I Go
- Writing Python like it's Rust
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Buck2, a large scale build tool written in Rust by Meta, is now available
Internally we use Pyre for Python type checking: https://github.com/facebook/pyre-check
- Are there any sectors that use Haskell as a main programming language?
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It is becoming difficult for me to be productive in Python
Before type hinting, work had intense rules and linters enforcing docstrings with types. Now, type hints and automatic pyre runs take care of all the heavy lifting.
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Ruby 3.2’s YJIT is Production-Ready
Python now has an optional type system and if you add one of them such as mypy or pyre to your CI process and you can configure GitHub to refuse the pull request until types are added you can make it somewhat strongly typed.
If you have a preexisting codebase I believe the way you can convert it is to add the types that you know on commits and eventually you will have enough types that adding the missing ones should be easy. For the missing ones Any is a good choice.
https://pyre-check.org and https://github.com/python/mypy are popular.
mamba
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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.
- FLaNK Stack 05 Feb 2024
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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
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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!
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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.
- Why train on Yi 4K instead of 200K?
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Show HN: Mamba-Chat – A Chat LLM Based on State Space Models
Hey everyone! Many of you might have come across the Mamba paper a few days ago, which introduced an LLM based on a state space model architecture. The Mamba architecture is quite useful as its complexity scales subquadratically with input length and is therefore way more efficient than transformer models: https://github.com/state-spaces/mamba
I got really excited about the paper, so I decided to fine-tune the model on a chat dataset. It turns that this actually worked quite well! The model is quite suitable for casual chatting, which honestly surprised me given that it only has 2.8B parameters and the base model was only trained on the Pile. It's quite exciting that we might have a serious candidate for an architecture that could dethrone transformers.
You can find both my fine-tuning and inference code here: https://github.com/havenhq/mamba-chat
What are some alternatives?
pyright - Static Type Checker for Python
mypy - Optional static typing for Python
pytype - A static type analyzer for Python code
typeshed - Collection of library stubs for Python, with static types
flake8
typing - Python static typing home. Hosts the documentation and a user help forum.
mamba - The Fast Cross-Platform Package Manager
psst - Fast and multi-platform Spotify client with native GUI
algoneer - The Algoneer Python library.
isort - A Python utility / library to sort imports.
ncspot - Cross-platform ncurses Spotify client written in Rust, inspired by ncmpc and the likes.
semgrep-rules - Semgrep rules registry