(Failed - but working 100%) Interview challenge
https://www.reddit.com/r/Python/comments/137gvt9/failed_but_working_100_interview_challenge/
https://www.reddit.com/r/Python/comments/137gvt9/failed_but_working_100_interview_challenge/
AutoGPTQ
An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
https://github.com/PanQiWei/AutoGPTQ
An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
https://github.com/PanQiWei/AutoGPTQ
GitHub
GitHub - AutoGPTQ/AutoGPTQ: An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm. - AutoGPTQ/AutoGPTQ
Representing Monetary Values in Python
Understanding how to accurately represent monetary values in Python is crucial for building financial applications, analyzing data, or simply improving your coding skills. This tutorial explores the various techniques and best practices for effectively working with money.
https://www.youtube.com/watch?v=0kzjD6jvfnk
Understanding how to accurately represent monetary values in Python is crucial for building financial applications, analyzing data, or simply improving your coding skills. This tutorial explores the various techniques and best practices for effectively working with money.
https://www.youtube.com/watch?v=0kzjD6jvfnk
YouTube
Representing Monetary Values in Python
Understanding how to accurately represent monetary values in Python is crucial for building financial applications, analyzing data, or simply improving your coding skills. In this tutorial, I'll explore the various techniques and best practices for effectively…
Blazing Fast ETLs with Simultaneous MultiProcessing and MultiThreading
The post delves into the techniques and benefits of using simultaneous multiprocessing and multithreading for ETL (Extract, Transform, Load) processes. It explores how leveraging these parallel processing approaches can significantly improve the performance and efficiency of ETL tasks, resulting in faster data processing and enhanced overall productivity.
https://heyashy.medium.com/blazing-fast-etls-with-simultaneous-multiprocessing-and-multithreading-214865b56516
The post delves into the techniques and benefits of using simultaneous multiprocessing and multithreading for ETL (Extract, Transform, Load) processes. It explores how leveraging these parallel processing approaches can significantly improve the performance and efficiency of ETL tasks, resulting in faster data processing and enhanced overall productivity.
https://heyashy.medium.com/blazing-fast-etls-with-simultaneous-multiprocessing-and-multithreading-214865b56516
Medium
Blazing Fast ETLs with Simultaneous MultiProcessing and MultiThreading
How I got a 66.4x reduction in code execution time
The Many Problems with Celery
The post discusses the challenges and limitations of using Celery, a distributed task queue framework in Python, highlighting issues related to scalability, error handling, and deployment complexities.
https://steve.dignam.xyz/2023/05/20/many-problems-with-celery/
The post discusses the challenges and limitations of using Celery, a distributed task queue framework in Python, highlighting issues related to scalability, error handling, and deployment complexities.
https://steve.dignam.xyz/2023/05/20/many-problems-with-celery/
Log Blog Kebab
The Many Problems with Celery
With some possible fixes
bigcode-project / starcoder
Home of StarCoder: fine-tuning & inference!
https://github.com/bigcode-project/starcoder
Home of StarCoder: fine-tuning & inference!
https://github.com/bigcode-project/starcoder
GitHub
GitHub - bigcode-project/starcoder: Home of StarCoder: fine-tuning & inference!
Home of StarCoder: fine-tuning & inference! Contribute to bigcode-project/starcoder development by creating an account on GitHub.
Olive
Olive is an easy-to-use hardware-aware model optimization tool that composes industry-leading techniques across model compression, optimization, and compilation.
https://github.com/microsoft/Olive
Olive is an easy-to-use hardware-aware model optimization tool that composes industry-leading techniques across model compression, optimization, and compilation.
https://github.com/microsoft/Olive
GitHub
GitHub - microsoft/Olive: Olive: Simplify ML Model Finetuning, Conversion, Quantization, and Optimization for CPUs, GPUs and NPUs.
Olive: Simplify ML Model Finetuning, Conversion, Quantization, and Optimization for CPUs, GPUs and NPUs. - microsoft/Olive
Sophia
Effortless plugin and play Optimizer to cut model training costs by 50%. New optimizer that is 2x faster than Adam on LLMs.
https://github.com/kyegomez/Sophia
Effortless plugin and play Optimizer to cut model training costs by 50%. New optimizer that is 2x faster than Adam on LLMs.
https://github.com/kyegomez/Sophia
GitHub
GitHub - kyegomez/Sophia: Effortless plugin and play Optimizer to cut model training costs by 50%. New optimizer that is 2x faster…
Effortless plugin and play Optimizer to cut model training costs by 50%. New optimizer that is 2x faster than Adam on LLMs. - kyegomez/Sophia
flood
flood is a load testing tool for benchmarking EVM nodes over RPC
https://github.com/paradigmxyz/flood
flood is a load testing tool for benchmarking EVM nodes over RPC
https://github.com/paradigmxyz/flood
GitHub
GitHub - paradigmxyz/flood: flood is a load testing tool for benchmarking EVM nodes over RPC
flood is a load testing tool for benchmarking EVM nodes over RPC - paradigmxyz/flood
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
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
www.devever.net
Writing a KVM hypervisor VMM in Python
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
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
Medium
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…
threestudio
A unified framework for 3D content generation.
https://github.com/threestudio-project/threestudio
A unified framework for 3D content generation.
https://github.com/threestudio-project/threestudio
GitHub
GitHub - threestudio-project/threestudio: A unified framework for 3D content generation.
A unified framework for 3D content generation. Contribute to threestudio-project/threestudio development by creating an account on GitHub.
string2string
String-to-String Algorithms for Natural Language Processing.
https://github.com/stanfordnlp/string2string
String-to-String Algorithms for Natural Language Processing.
https://github.com/stanfordnlp/string2string
GitHub
GitHub - stanfordnlp/string2string: String-to-String Algorithms for Natural Language Processing
String-to-String Algorithms for Natural Language Processing - stanfordnlp/string2string
Python 3.11.4, 3.10.12, 3.9.17, 3.8.17, 3.7.17, and 3.12.0 beta 2 are now available
https://pythoninsider.blogspot.com/2023/06/python-3114-31012-3917-3817-3717-and.html
https://pythoninsider.blogspot.com/2023/06/python-3114-31012-3917-3817-3717-and.html
Blogspot
Python Insider: Python 3.11.4, 3.10.12, 3.9.17, 3.8.17, 3.7.17, and 3.12.0 beta 2 are now available