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Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.
Lightning-fast serving engine for any AI model of any size. Flexible. Easy. Enterprise-scale.
[EMNLP'23, ACL'24] To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
IDE-style autocomplete for your existing terminal & shell
Parametrically designing my PhD thesis cover using adaptive sampling, neural networks, and quantum physics
Matplotlib styles for scientific plotting
An awesome iTerm2 backend for Matplotlib, so you can plot directly in your terminal.
📝A simple and elegant markdown editor, available for Linux, macOS and Windows.
Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
microsoft / vscode-python
Forked from DonJayamanne/pythonVSCodePython extension for Visual Studio Code
Create powerful Hydra applications without the yaml files and boilerplate code.
Machine learning metrics for distributed, scalable PyTorch applications.
Python toolbox for lighting and color science
METER: A Multimodal End-to-end TransformER Framework
Spectral optimisation pipeline for multi-primary LED lighting systems.
This reporsitory provides over 490,000 optimised multi-channel LED metamer spectra presented in the article "Optimising metameric spectra for integrative lighting to modulate the circadian system w…
Code accompanying my blog post: So, what is a physics-informed neural network?
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.
Statistical Rethinking course winter 2022
Python package for decomposing multi-dimensional arrays into sub-arrays (slices) according to multiple criteria.
Statistical package in Python based on Pandas