Results for “transformer-engine”

Resolves legacy references to the conversion-engineer capability by routing to the current runtime agent or skill.

Run state-of-the-art machine learning models directly in JavaScript/TypeScript across browsers and server-side runtimes using Transformers.js.

Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).

Orchestrate altering an existing, working feature to new desired behavior by updating tests first, then changing implementation, reviewing, and committing with gated approval.

PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production

Configure Unreal Engine core settings — rendering, physics, audio, garbage collection, console variables (cvars), and scalability levels (EngineSettingsService). Use when the user asks to change engine/rendering settings, set a console variable (r.*, etc.), adjust scalability/quality levels, or read engine config categories.

Expert skill for building web-based game engines and games using HTML5, Canvas, WebGL, and JavaScript. Use when asked to create games, build game engines, implement game physics, handle collision detection, set up game loops, manage sprites, add game controls, or work with 2D/3D rendering. Covers techniques for platformers, breakout-style games, maze games, tilemaps, audio, multiplayer via WebRTC, and publishing games.

Multimodal Learning with Transformers: A Survey

Add, remove, edit, list, or change the boot default of nvpmodel power modes on Jetson/Tegra platforms (Orin, Thor) by modifying the BSP-side configuration file.

Develop firmware for microcontrollers, implement RTOS applications, and optimize power consumption for resource-constrained devices.

Flame Engine 2D 遊戲開發完整指南 - 核心、系統、模板、部署

High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.