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@testflightynoti · Post #37881 · 05/09/2026, 05:04 PM
#NetBird#P2P#VPN Join the NetBird P2P VPN beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/jISzXOP8 Shared by Dimitri
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Source channel @githubtrending · Post #15340 · Dec 17
#python#gym#gym_environment#reinforcement_learning#reinforcement_learning_agent#reinforcement_learning_environments#rl_environment#rl_training NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior. https://github.com/NVIDIA-NeMo/Gym
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@githubtrending · Post #14789 · 06/05/2025, 11:30 AM
#go#golang#mesh#mesh_networks#nat_traversal#netbird#vpn#wireguard#wireguard_vpn#wiretrustee#zero_trust_network_access NetBird lets you quickly set up a secure private network for your organization or home without needing to configure complex firewall rules, open ports, or manage VPN gateways. It uses direct peer-to-peer connections based on WireGuard, so your devices connect to each other securely and efficiently, bypassing the need for a central server. You get strong security with features like access control, activity logging, and support for single sign-on, all managed from a simple web interface. This means you can connect and protect your devices anywhere, with minimal setup and maintenance, making remote access and network management much easier[2][1][5]. https://github.com/netbirdio/netbird