#python
Slime is a high-performance framework for post-training large language models with reinforcement learning (RL). It connects Megatron for fast training and SGLang for data generation, powering top models like GLM-4.7, Qwen3, DeepSeek V3, and Llama 3. You get efficient, flexible RL workflows with customizable data tools, cutting training time and boosting model accuracy for research or production—saving resources while achieving breakthrough results in physics, agents, and code generation.
https://github.com/THUDM/slime
Slime is a high-performance framework for post-training large language models with reinforcement learning (RL). It connects Megatron for fast training and SGLang for data generation, powering top models like GLM-4.7, Qwen3, DeepSeek V3, and Llama 3. You get efficient, flexible RL workflows with customizable data tools, cutting training time and boosting model accuracy for research or production—saving resources while achieving breakthrough results in physics, agents, and code generation.
https://github.com/THUDM/slime
GitHub
GitHub - THUDM/slime: slime is an LLM post-training framework for RL Scaling.
slime is an LLM post-training framework for RL Scaling. - THUDM/slime
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#python
WiFi DensePose uses WiFi signals and AI to detect human poses in real-time without cameras, tracking up to 10 people at 30 FPS with sub-50ms speed. Its Rust version boosts performance 810x faster, adds fall detection, activity tracking, and a disaster module for finding survivors under rubble via vital signs and 3D location. Install easily with `pip install wifi-densepose` for privacy-safe monitoring in homes, fitness, healthcare, or emergencies—saving lives and enhancing security without visual privacy risks.
https://github.com/ruvnet/wifi-densepose
WiFi DensePose uses WiFi signals and AI to detect human poses in real-time without cameras, tracking up to 10 people at 30 FPS with sub-50ms speed. Its Rust version boosts performance 810x faster, adds fall detection, activity tracking, and a disaster module for finding survivors under rubble via vital signs and 3D location. Install easily with `pip install wifi-densepose` for privacy-safe monitoring in homes, fitness, healthcare, or emergencies—saving lives and enhancing security without visual privacy risks.
https://github.com/ruvnet/wifi-densepose
GitHub
GitHub - ruvnet/wifi-densepose: Production-ready implementation of InvisPose - a revolutionary WiFi-based dense human pose estimation…
Production-ready implementation of InvisPose - a revolutionary WiFi-based dense human pose estimation system that enables real-time full-body tracking through walls using commodity mesh routers - ...
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#python #adblock #adblock_list #adblock_plus #adguard #adguard_list #adguardhome #quantumult_x
GOODBYEADS offers powerful, regularly updated rules (over 215,000 ad blocks, 102,000 DNS blocks) in formats like AdGuard, Quantumult X, and SmartDNS, with GitHub and fast domestic links. It blocks ads, trackers, and malware from top sources for clean browsing. You gain faster page loads, better privacy, less data use, and fewer distractions on any device.
https://github.com/8680/GOODBYEADS
GOODBYEADS offers powerful, regularly updated rules (over 215,000 ad blocks, 102,000 DNS blocks) in formats like AdGuard, Quantumult X, and SmartDNS, with GitHub and fast domestic links. It blocks ads, trackers, and malware from top sources for clean browsing. You gain faster page loads, better privacy, less data use, and fewer distractions on any device.
https://github.com/8680/GOODBYEADS
GitHub
GitHub - 8680/GOODBYEADS: 适用于AdGuard、Quantumult X、SmartDNS的去广告规则,合并优质上游规则并去重整理排列。
适用于AdGuard、Quantumult X、SmartDNS的去广告规则,合并优质上游规则并去重整理排列。 - 8680/GOODBYEADS
#python
This Claude Code Telegram Bot connects your Telegram messenger to Claude AI, letting you work with your code projects from anywhere without needing a terminal. You can chat naturally with Claude to analyze, edit, or explain your code, run tests, and manage files—all from your phone. The bot maintains conversation history for each project, so Claude remembers context between chats. It includes security features like user authentication and directory protection, plus it can handle webhooks and scheduled tasks. The main benefit is productivity on the go: you get AI-powered coding assistance instantly through a messaging app you already use daily, transforming your phone into a development tool.
https://github.com/RichardAtCT/claude-code-telegram
This Claude Code Telegram Bot connects your Telegram messenger to Claude AI, letting you work with your code projects from anywhere without needing a terminal. You can chat naturally with Claude to analyze, edit, or explain your code, run tests, and manage files—all from your phone. The bot maintains conversation history for each project, so Claude remembers context between chats. It includes security features like user authentication and directory protection, plus it can handle webhooks and scheduled tasks. The main benefit is productivity on the go: you get AI-powered coding assistance instantly through a messaging app you already use daily, transforming your phone into a development tool.
https://github.com/RichardAtCT/claude-code-telegram
GitHub
GitHub - RichardAtCT/claude-code-telegram: A powerful Telegram bot that provides remote access to Claude Code, enabling developers…
A powerful Telegram bot that provides remote access to Claude Code, enabling developers to interact with their projects from anywhere with full AI assistance and session persistence. - RichardAtCT/...
#python #bytetrack #multi_object_tracking #oc_sort #sort
Trackers is a simple Python library (pip install trackers) for multi-object tracking that plugs into any detection model like YOLO. Use it via CLI on videos/webcams or in Python code with trackers like ByteTrack (top performer on MOT17/SportsMOT benchmarks) to add labels and trajectories. Evaluate with MOT metrics too. Benefit: Quickly add reliable object tracking to your computer vision projects for real-time apps like traffic or sports analysis, saving time on custom code.
https://github.com/roboflow/trackers
Trackers is a simple Python library (pip install trackers) for multi-object tracking that plugs into any detection model like YOLO. Use it via CLI on videos/webcams or in Python code with trackers like ByteTrack (top performer on MOT17/SportsMOT benchmarks) to add labels and trajectories. Evaluate with MOT metrics too. Benefit: Quickly add reliable object tracking to your computer vision projects for real-time apps like traffic or sports analysis, saving time on custom code.
https://github.com/roboflow/trackers
GitHub
GitHub - roboflow/trackers: Trackers gives you clean, modular re-implementations of leading multi-object tracking algorithms released…
Trackers gives you clean, modular re-implementations of leading multi-object tracking algorithms released under the permissive Apache 2.0 license. You combine them with any detection model you alre...
#python
Hugging Face Skills are ready-to-use folders with instructions, scripts, and tools for AI agents to handle tasks like creating datasets, training models, running evaluations, managing jobs, and publishing papers. They work seamlessly with tools like Claude Code, OpenAI Codex, Gemini CLI, and Cursor—just install via simple commands and mention the skill in your instructions, such as "Use the HF model trainer skill." This saves you time by automating complex Hugging Face Hub operations, letting your agent execute them accurately without manual coding.
https://github.com/huggingface/skills
Hugging Face Skills are ready-to-use folders with instructions, scripts, and tools for AI agents to handle tasks like creating datasets, training models, running evaluations, managing jobs, and publishing papers. They work seamlessly with tools like Claude Code, OpenAI Codex, Gemini CLI, and Cursor—just install via simple commands and mention the skill in your instructions, such as "Use the HF model trainer skill." This saves you time by automating complex Hugging Face Hub operations, letting your agent execute them accurately without manual coding.
https://github.com/huggingface/skills
GitHub
GitHub - huggingface/skills
Contribute to huggingface/skills development by creating an account on GitHub.
#python #agents #claude #cursor #databricks #vibecoding
The Databricks AI Dev Kit enhances AI-driven development by providing your coding assistant (Claude Code, Cursor, etc.) with trusted Databricks knowledge and best practices. It includes a Python library, MCP server with 50+ tools, markdown skills teaching Databricks patterns, and a web-based builder app. You can build Spark pipelines, jobs, dashboards, knowledge assistants, and deploy ML models faster and smarter. The benefit is that your AI coding assistant gains direct access to Databricks functionality and patterns, enabling you to develop data and AI applications more efficiently with built-in governance and best practices.
https://github.com/databricks-solutions/ai-dev-kit
The Databricks AI Dev Kit enhances AI-driven development by providing your coding assistant (Claude Code, Cursor, etc.) with trusted Databricks knowledge and best practices. It includes a Python library, MCP server with 50+ tools, markdown skills teaching Databricks patterns, and a web-based builder app. You can build Spark pipelines, jobs, dashboards, knowledge assistants, and deploy ML models faster and smarter. The benefit is that your AI coding assistant gains direct access to Databricks functionality and patterns, enabling you to develop data and AI applications more efficiently with built-in governance and best practices.
https://github.com/databricks-solutions/ai-dev-kit
GitHub
GitHub - databricks-solutions/ai-dev-kit: Databricks Toolkit for Coding Agents provided by Field Engineering
Databricks Toolkit for Coding Agents provided by Field Engineering - databricks-solutions/ai-dev-kit