flood

flood is a load testing tool for benchmarking EVM nodes over RPC

https://github.com/paradigmxyz/flood

chatdocs

Chat with your documents offline using AI.

https://github.com/marella/chatdocs

Writing a KVM hypervisor VMM in Python

An experimental VMM for KVM written in Python. This is simply an experimental proof of concept which was hacked together enough to be able to boot OVMF, then install Linux on a disk and boot it.

https://www.devever.net/~hl/kvm

JupyterLab 4.0 is Here

The Jupyter contributor community is proud to announce JupyterLab 4.0, the next major release of our full-featured development environment. The package is now available on PyPI and conda-forge. You can upgrade by running pip install --upgrade jupyterlab or conda install -c conda-forge jupyterlab.

https://blog.jupyter.org/jupyterlab-4-0-is-here-388d05e03442

threestudio

A unified framework for 3D content generation.

https://github.com/threestudio-project/threestudio

string2string

String-to-String Algorithms for Natural Language Processing.

https://github.com/stanfordnlp/string2string

PyStack

PyStack is a tool that uses forbidden magic to let you inspect the stack frames of a running Python process or a Python core dump, helping you quickly and easily learn what it's doing (or what it was doing when it crashed) without having to interpret nasty CPython internals.

https://github.com/bloomberg/pystack

Lanarky

Lanarky is an open-source framework to deploy LLM applications in production. It is built on top of FastAPI and comes with batteries included.

https://github.com/ajndkr/lanarky

Refactoring a Command Line Shell | Code Roast Part 1

Watch the video to witness the transformation from average to exceptional code in Part 1 of 2 videos.

https://www.youtube.com/watch?v=TDgouhWA13A

PyCon US 2023 Video

Recordings from PyCon US 2023 in Salt Lake City, UT.

https://www.youtube.com/playlist?list=PL2Uw4_HvXqvY2zhJ9AMUa_Z6dtMGF3gtb

Don’t let yourself be fooled by data drift

The purpose of this post is to demonstrate that not all data drift impacts model performance. Making drift methods hard to trust since they tend to produce a large number of false alarms. To illustrate this point, we will train an ML model using a real-world dataset, monitor the distribution of the model's features in production, and report any data drift that might occur.

https://www.nannyml.com/blog/when-data-drift-does-not-affect-performance-machine-learning-models

Hiera

A Hierarchical Vision Transformer without the Bells-and-Whistles.

https://github.com/facebookresearch/hiera

roop

one-click deepfake (face swap)

https://github.com/s0md3v/roop

survey

A simple library for creating beautiful interactive prompts.

https://github.com/Exahilosys/survey