Python

As large language models (LLMs) continue to grow in scale, the cost of inference has skyrocketed. To enable models to respond to user requests faster and more economically, various optimization techniques have emerged. Among them, KV-Cache (Key-Value Cache) stands out as one of the most critical and impactful inference acceleration mechanisms, widely adopted by all major inference frameworks (e.g., vLLM, TensorRT-LLM, LLama.cpp, llm-d, OpenAI Triton Transformer Engine, etc.). This article provides a comprehensive introduction to what KV-Cache is, how it works, why it significantly improves inference efficiency, its impact on the industry, and best practices for its use....

With Azure AI Foundry opening support for Sora 2 (OpenAI’s generative video model), developers can now access top-tier video generation capabilities in an enterprise-grade, compliant, and controllable environment. This tutorial will take you from zero to production, showing how to call Sora 2 via the Playground and the Python SDK to complete a “text-to-video” workflow. Prerequisites Before starting, you need: Get an Azure subscription You need an Azure subscription. If you’re unsure how to get one, refer to the subscription registration section in my earlier article....

Large language models often encounter GPU memory bottlenecks during inference deployment: Model parameters (P) can reach hundreds of GB and must remain resident in GPU memory. Input/output data (D) changes dynamically with each request but is often coupled with parameters on the same device, leading to imbalanced memory usage and limited scalability. To solve this problem, we can leverage the vLLM framework to implement Parameter/Data (P/D) Separation, improving the flexibility and throughput of inference systems....

What is VibeVoice? VibeVoice is a research framework released by Microsoft Research for long-form, multi-speaker, conversational speech synthesis. Target scenarios include entire podcast episodes, audio dramas, or interviews: it can maintain speaker consistency within a single generation and handle natural turn-taking. The model family includes multiple scales (e.g., 1.5B, 7B, etc.) and is available on Hugging Face as microsoft/VibeVoice-1.5B, along with model cards, weights, installation guides, and responsible use notes....

As large language models (LLMs) grow in popularity, the focus for enterprises and individuals has shifted from training to inference (in other words, moving from “building wheels” to practical usage). In the field of inference, the two hottest frameworks are undoubtedly vLLM and SGLang. As a rising star, SGLang has also attracted attention. Today, we’ll explore SGLang through a beginner-friendly tutorial to help more people understand both LLM inference and the SGLang framework....