#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
EVAA: Introducing Loop APY for LP Pool Interface
#Loop#EVAA
EVAA introduces a new Loop APY feature in its LP Pool Interface, enabling users to deposit LP tokens from StormTrade or DeDust as collateral, borrow TON or USDT, and utilize a liquidity looping strategy to potentially enhance annual returns. This strategy combines third-party yields, EVAA rates, and compounding effects.
Source: link
@tonlines
For operatori
Umuman olganda kod yozayotganingizda bir xil hisoblash jarayonini qayta-qayta yozish qimmatli vaqtingizni o'g'irlab sizni bezor qilishi mumkin, masalan siz “Salom, Dunyo!” jumlasini 100 marta yozishingiz zarur bo’lib qoldi.Siz uni qayta qayta yozib chiqgan bo’larmidingiz, yo’q albatta.
👉Batafsil
👨🏫 Mentor: Suxrob Xayitmurodov
#csharp#for#loop#starter
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