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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 #15367 · 12/25/2025, 01:00 PM

#cplusplus#arduino#ble_jammer#ble_spoof#ble_spoofer#cybersecurity#deauther#esp32#hack#hacktoberfest#jammer#nrf_scanner#nrf24l01#sour_apple nRFBOX is a handheld ESP32-based tool that scans and analyzes the 2.4 GHz band (Wi‑Fi, BLE, etc.), shows signal strength and channel activity, and can run jamming, BLE jamming/spoofing, and Wi‑Fi deauthentication tests for security research and troubleshooting. It combines an ESP32, NRF24 modules, OLED display, battery management, and SD support for firmware and logging, with notes about limited range, device variability, and power limits when using multiple NRF modules. Benefit: you can use it to find crowded channels, diagnose wireless interference, and test network/device resilience in controlled, legal test environments. https://github.com/cifertech/nRFBox