mamba
pip-tools
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mamba | pip-tools | |
---|---|---|
15 | 58 | |
9,307 | 7,472 | |
26.9% | 1.1% | |
8.3 | 8.9 | |
8 days ago | 10 days ago | |
Python | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" 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
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Based: Simple linear attention language models
> how the recall can grow unbounded with no tradeoff
this? https://github.com/state-spaces/mamba/issues/175
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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.
[0]: https://github.com/state-spaces/mamba
- FLaNK Stack 05 Feb 2024
- Introduction to State Space Models (SSM)
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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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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
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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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[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:
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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.
pip-tools
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Pyenv – lets you easily switch between multiple versions of Python
> Why is the "requirements.txt" file a stupid flat listing of all transitive dependencies with pinned versions? It makes it harder to change library versions even if there are no true conflicts.
My friend, here is what you seek: https://github.com/jazzband/pip-tools
requirements.txt is flat because it's really the output of `pip freeze`. It's supposed to completely and exactly rebuild the environment. Unfortunately it's far too flexible and people abuse it by putting in only direct dependencies etc.
If you're writing packages, you don't need a requirements.txt at all, by the way. Package dependencies (only direct dependencies) live in pyproject.toml with the rest of the package config. requirements.txt (and pip tools) are only for when you want to freeze the whole environment, like for a server deployment.
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lockfiles for hatch projects
For all my projects I found myself regenerating manual lock files using complex shell commands with pip-compile to get a reproducible environments across devices using a custom pre-install-command. I finally decided that instead of hacking together the same solution on all my projects I would build a plugin that handles this complexity for me.
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Setting up Django in a Better Way in 5 Minutes and Understanding How It Works
Instead of venv, we are using pip-tools in this starter kit. pip-tools take things further in dependency management. Check out what pip-tools does in their official GitHub repo. In short, it helps your project find the best match for the dependent packages. For example, you might need two packages A and B in your project that requires same package C under the hood. But A requires any version of C from 1.0.1 to 1.0.10 and B requires any version of C from 1.0.7 to 1.0.15. Pip tools will automatically compile the version of 'C' that suits for both of your packages.
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just-pip-tools: An example of managing python dependencies as layered lock files with just and pip-tools
I've created a small project called just-pip-tools that combines pip-tools and just to manage Python dependencies in a layered approach. This isn't a magic bullet; it's a set of files you can adapt to your needs.
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Maintaining virtual environments
For small projects I recommend pip-tools. Just write packet list in requirements.in and pip-compile compile a requirements.txt with comments.
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how to upgrade psycopg2 to psycopg3 as per django latest documentation
Take a look at pip-tools, great package. https://github.com/jazzband/pip-tools
- Single-file scripts that download their dependencies
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What are people using to organize virtual environments these days?
pip-tools
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How to know what a package depend on when pip is installing it?
I recommend generating a lockfile to document this information, as you might do with pip-tools.
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A not so unfortunate sharp edge in Pipenv
Check out pip-tools [1] which does exactly that, albeit in a slightly more polished way.
[1]: https://github.com/jazzband/pip-tools
What are some alternatives?
miniforge - A conda-forge distribution.
Poetry - Python packaging and dependency management made easy
pip - The Python package installer
PDM - A modern Python package and dependency manager supporting the latest PEP standards
llm.f90 - LLM inference in Fortran
Pipenv - Python Development Workflow for Humans.
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
mamba-chat - Mamba-Chat: A chat LLM based on the state-space model architecture 🐍
spack - A flexible package manager that supports multiple versions, configurations, platforms, and compilers.