Mobile-VideoGPT
Fast and Accurate Video Understanding Language Model.
https://github.com/amshaker/mobile-videogpt
Fast and Accurate Video Understanding Language Model.
https://github.com/amshaker/mobile-videogpt
GitHub
GitHub - Amshaker/Mobile-VideoGPT: Mobile-VideoGPT: Fast and Accurate Video Understanding Language Model
Mobile-VideoGPT: Fast and Accurate Video Understanding Language Model - Amshaker/Mobile-VideoGPT
Inside the CodeBot: A Gentle Introduction to How LLMs Understand Nullability
The article explores how large language models (LLMs) comprehend the concept of nullability in programming. It discusses methods for evaluating LLMs' understanding of nullable types and introduces techniques to probe their internal representations regarding null values.
https://dmodel.ai/nullability-gentle/
The article explores how large language models (LLMs) comprehend the concept of nullability in programming. It discusses methods for evaluating LLMs' understanding of nullable types and introduces techniques to probe their internal representations regarding null values.
https://dmodel.ai/nullability-gentle/
dmodel.ai
Inside the CodeBot: A Gentle Introduction to How LLMs Understand Nullability
Shadowing in Python gave me an UnboundLocalError
This article discusses a common Python pitfall where shadowing a variable within a function can lead to an UnboundLocalError due to Python's scoping rules. It explains that if a variable is bound anywhere in a function, it's considered local to the entire function, even before it's initialized, which can cause unexpected errors.
https://ntietz.com/blog/pythons-shadowing-behavior-always-surprises-me/
This article discusses a common Python pitfall where shadowing a variable within a function can lead to an UnboundLocalError due to Python's scoping rules. It explains that if a variable is bound anywhere in a function, it's considered local to the entire function, even before it's initialized, which can cause unexpected errors.
https://ntietz.com/blog/pythons-shadowing-behavior-always-surprises-me/
Django: what’s new in 5.2
This post highlights key new features in Django 5.2, including automatic model importing in the shell, support for composite primary keys, and a simplified way to override BoundField on forms.
https://adamj.eu/tech/2025/04/07/django-whats-new-5.2/
This post highlights key new features in Django 5.2, including automatic model importing in the shell, support for composite primary keys, and a simplified way to override BoundField on forms.
https://adamj.eu/tech/2025/04/07/django-whats-new-5.2/
adamj.eu
Django: what’s new in 5.2 - Adam Johnson
Django 5.2 was released last Wednesday, another exciting step forward for our favourite web framework. It comes with a composite of new features, contributed to by many, some of which I am happy to have helped with. Below is my pick of highlights from the…
no-code-architects-toolkit
The NCA Toolkit API eliminates monthly subscription fees by consolidating common API functionalities into a single FREE API. Designed for businesses, creators, and developers, it streamlines advanced media processing, including video editing and captioning, image transformations, cloud storage, and Python code execution.
https://github.com/stephengpope/no-code-architects-toolkit
The NCA Toolkit API eliminates monthly subscription fees by consolidating common API functionalities into a single FREE API. Designed for businesses, creators, and developers, it streamlines advanced media processing, including video editing and captioning, image transformations, cloud storage, and Python code execution.
https://github.com/stephengpope/no-code-architects-toolkit
GitHub
GitHub - stephengpope/no-code-architects-toolkit: The NCA Toolkit API eliminates monthly subscription fees by consolidating common…
The NCA Toolkit API eliminates monthly subscription fees by consolidating common API functionalities into a single FREE API. Designed for businesses, creators, and developers, it streamlines advanc...
Slipstream - a python library for stateful stream processing
https://slipstream.readthedocs.io/en/1.0.1/
https://slipstream.readthedocs.io/en/1.0.1/
adk-python
An open-source, code-first Python toolkit by Google for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
https://github.com/google/adk-python
An open-source, code-first Python toolkit by Google for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
https://github.com/google/adk-python
GitHub
GitHub - google/adk-python: An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI…
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. - google/adk-python
Build a Desktop Sticky Notes Application with PySide6 & SQLAlchemy
This post provides a step-by-step guide to creating a desktop sticky notes application using PySide6, covering GUI setup, styling, and adding functionality like movable notes and a system tray icon. It explains how to build a simple, frameless note window, enable dragging, and manage multiple notes, with code examples for each stage.
https://www.pythonguis.com/examples/pyside6-desktop-sticky-notes/
This post provides a step-by-step guide to creating a desktop sticky notes application using PySide6, covering GUI setup, styling, and adding functionality like movable notes and a system tray icon. It explains how to build a simple, frameless note window, enable dragging, and manage multiple notes, with code examples for each stage.
https://www.pythonguis.com/examples/pyside6-desktop-sticky-notes/
Python GUIs
Build a Desktop Sticky Notes Application with PySide6 & SQLAlchemy
Build a desktop sticky notes application with Python and Qt6. Persistent note storage with SQLAlchemy and SQLite. Do you ever find yourself needing to take a quick note of some information but have nowhere to put it? Then this app is for you! This virtual…
Reproducing word2vec with JAX
This article reproduces the word2vec model using JAX, explaining the CBOW architecture and its implementation. It trains word embeddings and demonstrates how to find word similarities and analogies using the trained model, comparing it to modern text embeddings used in LLMs.
https://eli.thegreenplace.net/2025/reproducing-word2vec-with-jax/
This article reproduces the word2vec model using JAX, explaining the CBOW architecture and its implementation. It trains word embeddings and demonstrates how to find word similarities and analogies using the trained model, comparing it to modern text embeddings used in LLMs.
https://eli.thegreenplace.net/2025/reproducing-word2vec-with-jax/
nano-aha-moment
Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for LLMs"
https://github.com/McGill-NLP/nano-aha-moment
Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for LLMs"
https://github.com/McGill-NLP/nano-aha-moment
GitHub
GitHub - McGill-NLP/nano-aha-moment: Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for…
Single File, Single GPU, From Scratch, Efficient, Full Parameter Tuning library for "RL for LLMs" - McGill-NLP/nano-aha-moment
I made a simple Artificial Life simulation software with python
https://www.reddit.com/r/Python/comments/1jwzv2h/i_made_a_simple_artificial_life_simulation/
https://www.reddit.com/r/Python/comments/1jwzv2h/i_made_a_simple_artificial_life_simulation/
Reddit
From the Python community on Reddit: I made a simple Artificial Life simulation software with python
Explore this post and more from the Python community
arxiv-mcp-server
A Model Context Protocol server for searching and analyzing arXiv papers.
https://github.com/blazickjp/arxiv-mcp-server
A Model Context Protocol server for searching and analyzing arXiv papers.
https://github.com/blazickjp/arxiv-mcp-server
GitHub
GitHub - blazickjp/arxiv-mcp-server: A Model Context Protocol server for searching and analyzing arXiv papers
A Model Context Protocol server for searching and analyzing arXiv papers - blazickjp/arxiv-mcp-server
memo
Memo is a simple command-line interface (CLI) tool for managing your Apple Notes (and eventually Apple Reminders). It’s written in Python and aims to offer a fast, keyboard-driven way to create, search, and organize notes and reminders straight from your terminal.
https://github.com/antoniorodr/memo
Memo is a simple command-line interface (CLI) tool for managing your Apple Notes (and eventually Apple Reminders). It’s written in Python and aims to offer a fast, keyboard-driven way to create, search, and organize notes and reminders straight from your terminal.
https://github.com/antoniorodr/memo
GitHub
GitHub - antoniorodr/memo: Memo is a simple command-line interface (CLI) tool for managing your Apple Notes and Apple Reminders.…
Memo is a simple command-line interface (CLI) tool for managing your Apple Notes and Apple Reminders. It’s written in Python and aims to offer a fast, keyboard-driven way to create, search, and org...
curl-impersonate
A special build of curl that can impersonate Chrome & Firefox.
https://github.com/lwthiker/curl-impersonate
A special build of curl that can impersonate Chrome & Firefox.
https://github.com/lwthiker/curl-impersonate
GitHub
GitHub - lwthiker/curl-impersonate: curl-impersonate: A special build of curl that can impersonate Chrome & Firefox
curl-impersonate: A special build of curl that can impersonate Chrome & Firefox - lwthiker/curl-impersonate
Code DeepSeek V3 From Scratch in Python
This video provides a comprehensive, step-by-step coding guide to understanding and implementing DeepSeek V3, a cutting-edge deep learning model. It covers key concepts like the attention mechanism, multihead latent attention (MLA), rotary positional embeddings (RoPE), and the mixture of experts (MoE) architecture, explaining the science behind it all.
https://www.youtube.com/watch?v=5avSMc79V-w
This video provides a comprehensive, step-by-step coding guide to understanding and implementing DeepSeek V3, a cutting-edge deep learning model. It covers key concepts like the attention mechanism, multihead latent attention (MLA), rotary positional embeddings (RoPE), and the mixture of experts (MoE) architecture, explaining the science behind it all.
https://www.youtube.com/watch?v=5avSMc79V-w
YouTube
Code DeepSeek V3 From Scratch in Python - Full Course
This course is a comprehensive guide to understanding and implementing DeepSeek V3, a cutting-edge deep learning model. @vukrosic shares step-by-step coding instructions and theoretical insights.
🔗 paper - https://arxiv.org/pdf/2412.19437
💻 https://git…
🔗 paper - https://arxiv.org/pdf/2412.19437
💻 https://git…
llm-compressor
Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM.
https://github.com/vllm-project/llm-compressor
Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM.
https://github.com/vllm-project/llm-compressor
GitHub
GitHub - vllm-project/llm-compressor: Transformers-compatible library for applying various compression algorithms to LLMs for optimized…
Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM - vllm-project/llm-compressor
VeOmni
Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework.
https://github.com/ByteDance-Seed/VeOmni
Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework.
https://github.com/ByteDance-Seed/VeOmni
GitHub
GitHub - ByteDance-Seed/VeOmni: VeOmni: Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework
VeOmni: Scaling any Modality Model Training to any Accelerators with PyTorch native Training Framework - ByteDance-Seed/VeOmni
User Onboarding Tips and Tricks for Django Developers
This video explains how to implement anonymous onboarding in Django apps, allowing users to try the app without creating an account. It covers storing temporary data in the session and seamlessly transferring it to a user account once created, enhancing the initial user experience.
https://www.youtube.com/watch?v=gFnE6a9-kLw
This video explains how to implement anonymous onboarding in Django apps, allowing users to try the app without creating an account. It covers storing temporary data in the session and seamlessly transferring it to a user account once created, enhancing the initial user experience.
https://www.youtube.com/watch?v=gFnE6a9-kLw
YouTube
User Onboarding Tips and Tricks for Django Developers
In this video I run through some of the details of the onboarding flow for my new app, Life in Weeks, which one person said "made the difference between me trying it at all versus sending the app to a few friends."
The key is letting people play with the…
The key is letting people play with the…