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Source channel @githubtrending · Post #15263 · Nov 2

#python#deep_learning#inference#llm#nlp#pytorch#transformer Nano-vLLM is a small, fast, and easy-to-understand tool for running large language models offline. It matches the speed of bigger systems like vLLM but uses only about 1,200 lines of clean Python code, making it simple to read and modify. It includes smart features like prefix caching and tensor parallelism to boost performance. You can install it easily and run models like Qwen3-0.6B on your own GPU. This tool is great if you want fast, efficient AI inference without complex setups, ideal for learning, research, or small deployments on limited hardware. https://github.com/GeeeekExplorer/nano-vllm

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Crypto M - Crypto News

@CryptoM · Post #64877 · 04/10/2026, 06:14 AM

🚀 Starknet Opens Voting on v0.14.2 Upgrade Proposal Starknet has announced that voting is now open for STRK holders on the v0.14.2 upgrade proposal. According to Foresight News, the voting period will end on April 16. The proposed upgrade includes the introduction of SNIP-36, SNIP-37, and SNIP-13, and aims to enable protocol-level S-Two proof verification, significantly reducing costs for privacy use cases and zk-thread applications. Additionally, the upgrade seeks to adjust the storage economic model to more accurately reflect network resource usage while maintaining cost advantages for developers. The StarkGate token contract will also be upgraded to optimize ERC-20 event indexing, verification, and token handling. Other internal upgrades are planned to prepare for the decentralized verification phase described in SNIP-33, including improvements in P2P, weighted proposer sampling, and the concept of virtual proposers. #Starknet#STRK#v0.14.2 #SNIP36#SNIP37#SNIP13#STwoProof#PrivacyUseCases#zkThread#StorageEconomicModel#StarkGate#ERC20#P2P#DecentralizedVerification#SNIP33#VirtualProposers