#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: WiFi DensePose turns commodity WiFi signals into real-time human pose estimation, vital sign monitoring…
WiFi DensePose turns commodity WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection — all without a single pixel of video. - GitHub - ruvnet/wifi-densep...
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