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stupe    
n. 湿布;热湿布;傻瓜;笨蛋

湿布;热湿布;傻瓜;笨蛋

stupe
n 1: a person who is not very bright; "The economy, stupid!"
[synonym: {stupid}, {stupid person}, {stupe}, {dullard},
{dolt}, {pudding head}, {pudden-head}, {poor fish},
{pillock}]


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英文字典中文字典相关资料:


  • GitHub - sgl-project sglang: SGLang is a high-performance serving . . .
    SGLang is a high-performance serving framework for large language models and multimodal models It is designed to deliver low-latency and high-throughput inference across a wide range of setups, from a single GPU to large distributed clusters
  • sglang README. md at main · sgl-project sglang · GitHub
    SGLang is a high-performance serving framework for large language models and multimodal models - sglang README md at main · sgl-project sglang
  • Materials for learning SGLang - GitHub
    The SGLang team is delighted to announce that SGLang has become the first fully open-source LLM serving engine to support large-scale Expert-Parallelism (EP) and Prefill-Decode disaggregation, achieving throughput that matches the performance reported in the DeepSeek official blog The cost has been reduced to $0 20 per 1M output tokens For more details, please refer to our LMSYS blog and the
  • sgl-project mini-sglang - GitHub
    A lightweight yet high-performance inference framework for Large Language Models Mini-SGLang is a compact implementation of SGLang, designed to demystify the complexities of modern LLM serving systems With a compact codebase of ~5,000 lines of Python, it serves as both a capable inference engine
  • sgl-project · GitHub
    SGLang is a high-performance serving framework for large language models and multimodal models Python 25k 5k sgl-learning-materials Public Materials for learning SGLang 786 60 ome Public
  • GitHub - QwenLM Qwen3. 5: Qwen3. 5 is the large language model series . . .
    SGLang SGLang is a fast serving framework for large language models and vision language models SGLang could be used to launch a server with OpenAI-compatible API service
  • GitHub - sgl-project sglang-jax: JAX backend for SGL
    SGL-JAX is a high-performance, JAX-based inference engine for Large Language Models (LLMs), specifically optimized for Google TPUs It is engineered from the ground up to deliver exceptional throughput and low latency for the most demanding LLM serving workloads The engine incorporates state-of-the
  • GitHub - sgl-project sglang-omni: SGLang Omni: High-Performance Multi . . .
    SGLang-Omni is an ecosystem project for SGLang Omni models refer to models that have multi-modal inputs and multi-modal outputs These models typically consist of multiple stages, making SGLang's LLM-specific architecture no longer suitable Therefore, SGLang-Omni is designed to provide the ability to orchestrate multi-stage pipeline with high performance and real-time API support Our core
  • SGLang Code Walk Through - GitHub
    SGLang Code Walk Through English version | 简体中文 This doc serve as a developer-level guidance and provide a brief code walkthrough of SGLang's backend, tracing the path of how requests are processed, as shown in the following figure
  • GitHub - sgl-project SpecForge: Train speculative decoding models . . .
    Train speculative decoding models effortlessly and port them smoothly to SGLang serving - sgl-project SpecForge





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