Topic: vllm Goto Github
Some thing interesting about vllm
Some thing interesting about vllm
vllm,
Organization: agnostiqhq
Home Page: https://www.covalent.xyz/
vllm,A simple service that integrates vLLM with Ray Serve for fast and scalable LLM serving.
User: asprenger
vllm,Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought, Instruction-Tuning and Multimodality.
User: atfortes
vllm,🔒 Enterprise-grade API gateway that helps you monitor and impose cost or rate limits per API key. Get fine-grained access control and monitoring per user, application, or environment. Supports OpenAI, Azure OpenAI, Anthropic, vLLM, and open-source LLMs.
Organization: bricks-cloud
Home Page: https://trybricks.ai/
vllm,Carbon Limiting Auto Tuning for Kubernetes
Organization: climatik-project
vllm,📖A curated list of Awesome LLM Inference Paper with codes, TensorRT-LLM, vLLM, streaming-llm, AWQ, SmoothQuant, WINT8/4, Continuous Batching, FlashAttention, PagedAttention etc.
User: deftruth
Home Page: https://github.com/DefTruth/Awesome-LLM-Inference
vllm,Preserving entities through the integration of knowledge graphs, Llama 2, vLLM, and LangChain.
User: esmailza
vllm,A library to benchmark LLMs via their API exposure
Organization: france-travail
vllm,A REST API for vLLM, production ready
Organization: france-travail
Home Page: https://france-travail.github.io/happy_vllm/
vllm,EchoSight is a tool that helps visually impaired individuals by audibly describing images taken with a Raspberry Pi Camera or inputted via image path or URL across different operating systems.
User: gusanmaz
vllm,Run code inference-only benchmarks quickly using vLLM
User: ineil77
vllm,Ready-to-deploy Docker image for Functionary LLM served as an OpenAI-Compatible API.
User: ivangabriele
vllm,Pre-loaded LLMs served as an OpenAI-Compatible API via Docker images.
User: ivangabriele
vllm,Setup and run a local LLM and Chatbot using consumer grade hardware.
User: jasonacox
vllm,Standardized spec and vendor-specific transforms for ChatML
Organization: julep-ai
Home Page: https://standard-chatml.org/
vllm,An simple implementation of Unet because all the implementations i've seen are wayy tooo complicated.
User: kyegomez
Home Page: https://discord.gg/qUtxnK2NMf
vllm,A Large Language Model based tool for generating human like responses to natural language inputs for network not connected over internet.
User: lklivingstone
Home Page: https://scotts-tots.netlify.app/
vllm,vLLM Router
Organization: llm-inference-router
vllm,Cog wrapper for deepseek-ai/deepseek-67b-base
User: lucataco
Home Page: https://replicate.com/lucataco/deepseek-67b-base
vllm,Cog wrapper for NousResearch/Hermes-2-Pro-Llama-3-8B
User: lucataco
Home Page: https://replicate.com/lucataco/hermes-2-pro-llama-3-8b
vllm,Cog wrapper for NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO
User: lucataco
Home Page: https://replicate.com/lucataco/nous-hermes-2-mixtral-8x7b-dpo
vllm,Cog wrapper for vllm implementation of Qwen/Qwen1.5-32B
User: lucataco
Home Page: https://replicate.com/lucataco/qwen1.5-32b
vllm,Cog wrapper for cognitivecomputations/Wizard-Vicuna-13B-Uncensored
User: lucataco
Home Page: https://replicate.com/lucataco/wizard-vicuna-13b-uncensored
vllm,This repository demonstrates LLM execution on CPUs using packages like llamafile, emphasizing low-latency, high-throughput, and cost-effective benefits for inference and serving.
User: mddunlap924
vllm,Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment. Demo apps to showcase Meta Llama3 for WhatsApp & Messenger.
Organization: meta-llama
vllm,A large-scale simulation framework for LLM inference
Organization: microsoft
vllm,AI-Learning-Platform, a LLM-RAG pipeline which behaves like a guide and able to solve doubts. Deployed on-premise IBM ppc64le architecture. vLLM for model inference & Qdrant with Langchain for RAG Pipeline. Server written in django, postgres & cassandra as the sql & nosql databases.
User: navinkumarmnk
Home Page: https://megnav.com/portfolio/ai-learning-platform
vllm,Official implementation of "DoRA: Weight-Decomposed Low-Rank Adaptation"
User: nbasyl
Home Page: https://arxiv.org/abs/2402.09353
vllm,【深度学习模型部署框架】支持tensorflow/torch/tensorrt/vllm以及更多nn框架,支持dynamic batching、streaming模式,支持Python/C++双语言,可限制,可拓展,高性能。帮助用户快速地将模型部署到线上,并通过HTTP/RPC接口方式提供服务。
Organization: netease-media
Home Page: https://zhuanlan.zhihu.com/p/707491462
vllm,General Information, model certifications, and benchmarks for nm-vllm enterprise distributions
Organization: neuralmagic
Home Page: https://neuralmagic.github.io/nm-vllm-certs/
vllm,llm-inference is a platform for publishing and managing llm inference, providing a wide range of out-of-the-box features for model deployment, such as UI, RESTful API, auto-scaling, computing resource management, monitoring, and more.
Organization: opencsgs
vllm,An Easy-to-use, Scalable and High-performance RLHF Framework (70B+ PPO Full Tuning & Iterative DPO & LoRA & Mixtral)
Organization: openrlhf
Home Page: https://openrlhf.readthedocs.io/
vllm,Dockerized LLM inference server with constrained output (JSON mode), built on top of vLLM and outlines. Faster, cheaper and without rate limits. Compare the quality and latency to your current LLM API provider.
Organization: phospho-app
Home Page: https://phospho.ai
vllm,Evaluate your LLM's response with Prometheus and GPT4 💯
Organization: prometheus-eval
vllm,The RunPod worker template for serving our large language model endpoints. Powered by vLLM.
Organization: runpod-workers
vllm,Call many AIs from a single API.
Organization: timesurgelabs
vllm,Fine-tuning and serving LLMs on any cloud
Organization: trainy-ai
Home Page: https://llm-atc.readthedocs.io/en/latest/
vllm,Low latency JSON generation using LLMs ⚡️
User: varunshenoy
vllm,An endpoint server for efficiently serving quantized open-source LLMs for code.
User: wangcx18
vllm,Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop.
Organization: xorbitsai
Home Page: https://inference.readthedocs.io
vllm,Fully-featured, beautiful web interface for vLLM - built with NextJS.
User: yoziru
vllm,ICE-PIXIU:A Cross-Language Financial Megamodeling Framework
User: yy0649
Home Page: https://github.com/topics/nlp
vllm,大模型推理框架加速,让 LLM 飞起来
User: zrzrzrzrzrzrzr
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