NVIDIA Nemotron Nano 2 VL: The Open Source Engine Powering The New AI Factory Stop Wasting GPU Flops on Cold Starts: High Performance Inference with Model Streamer - AI Eng Paris In the video, we are going to use AutoGEN with Local LLMs using Runpods. We are going to use a cool interface on google
Github repo: Try it yourself: Substratus.ai lets This video shows how to install Streaming-LLM which StreamingLLM allows large language models to handle infinite text input
LLM Explained | What is LLM vLLM - Turbo Charge your LLM Inference Install vllm in Thor failed - Jetson Thor - NVIDIA Developer Forums
This video shows how to run vllm inference with AI models on CPU on your local system. It also shares vLLM optimizations for vLLM is an open-source library designed for fast and efficient serving of LLMs. It's specifically optimized for high-throughput inference. Discover vLLM, UC Berkeley's open-source library for fast LLM inference, featuring a PagedAttention algorithm for up to 24x
Streaming-LLM Local Installation in Linux and Windows Build an API for LLM Inference using Rust: Super Fast on CPU Ready to deploy AI models or run GPU-intensive workloads fast and affordably? This updated 2025 Quickstart tutorial walks you
Want to Run vLLM on a New 50 Series GPU? Qwen Code CLI + Qwen-3 Coder 🔥 | Better Than Claude Code? - Full Tutorial Add MCP Server to Any FastAPI App in 5 Minutes
Ever thought about build a real world application with LangChain, with multiple microservices, a real Frontend Framework and No need to wait for a stable release. Instead, install vLLM from source with PyTorch Nightly cu128 for 50 Series GPUs. People who are confused to what vLLM is this is the right video. Watch me go through vLLM, exploring what it is and how to use it
Deploying LLM Chat Bot Models To Production vLLM: Easily Deploying & Serving LLMs
LangChain provides a caching mechanism for LLMs (large language models). The benefits of caching in your LLM development Runpod Affiliate Link* *One Click Runpod Template*
LLM Deployment using vLLM — NVIDIA Dynamo Documentation How to Run vLLM on CPU - Full Setup Guide vLLM - Turbo Charge your LLM Inference Blog post: Github: Docs:
Qwen just launched a new AI powered CLI - Qwen Code CLI. In this video, let's see how to set it up and use it with the newest vLLM Quick Start#. Below we provide a guide that lets you run all of our the common deployment patterns on a single node. Start NATS and ETCD in the
Python FastAPI Tutorial: Build a REST API in 15 Minutes You should use LangChain's Caching! AutoGen with Local LLMs | Get Rid of OpenAI API Keys
How to Run LLM Locally with Docker Model Runner #docker #ai #llm vLLM vs Llama.cpp: Which Local LLM Engine Reigns in 2025? Boost Your AI Predictions: Maximize Speed with vLLM Library for Large Language Model Inference
Getting Started with Inference Using vLLM With the FastAPI-MCP package it's super easy to add an MCP server to an existing FastAPI app. In this video, I'll show you how to Watch this demo of llm-d, the open-source solution for running large language models on Kubernetes! What You'll Learn: Sample
Vllm Vs Triton | Which Open Source Library is BETTER in 2025? All You Need To Know About Running LLMs Locally
Meta's New AI 'Tool LLM' Outperforms Every AI So FarI! #metaai #ToolLLM #aiinnovation In the world of AI innovation, Meta has Double Inference Speed with AWQ Quantization AutoLLM: Create RAG Based LLM Web Apps in SECONDS!
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Ep 28. How to Host Open-Source LLM Models In this quickstart, you will pull a vLLM Docker image, configure it for Neuron devices, and start an inference server running vLLM. This process lets you deploy
Get started with just $10 at vLLM is a high-performance, open-source inference engine designed for fast Best Deals on Amazon: MY TOP PICKS + INSIDER DISCOUNTS: I
Read the full article with tables and commands: Agentic Framework LangGraph explained in 8 minutes | Beginners Guide Blog Post: In this video, we'll look at
Quickstart Tutorial to Deploy vLLM on Runpod Simple and easy explanation of LLM or Large Language Model in less than 5 minutes. In this short video, you will build an
[Usage]: when i learn quickstart,python vllm/examples Quickstart#. This guide will help you quickly get started with vLLM to perform: Offline batched inference. Online serving using OpenAI-compatible server
Get a quick high-level overview of the key concepts of the Prometheus monitoring system straight from the co-founder of Welcome to the future of app development! In this video, we'll dive into the incredible world of creating complex LLM (Language Docker's Model Runner enables developers to run large language models (LLMs) locally inside Docker Desktop. This makes it
AutoGEN with Local LLMs (RunPods) 😎 on Google Colabs | Easy Set up Join me for a quick walkthrough of the steps involved in running Docker GenAI Stack on a GPU Machine. We will run two capable
A Closer Look at the Docker GenAI Stack Steve Watt, PyTorch ambassador - Getting Started with Inference Using vLLM. According to the Quickstart - vLLM uv venv --python 3.12 --seed source .venv/bin/activate uv pip install vllm --torch-backend=auto report
vllm-project/vllm: A high-throughput and memory-efficient - GitHub What is vLLM & How do I Serve Llama 3.1 With It? API For Open-Source Models 🔥 Easily Build With ANY Open-Source LLM
LAUNCH YOUR FIRST GENAI PRODUCT IN 5 WEEKS WEBINAR: Multiple times available (click to register): February 27 at About. vLLM is a fast and easy-to-use library for LLM inference and serving. · Getting Started. Install vLLM with pip or from source: · Contributing. We welcome
Learn how to install and build your first app with FastAPI (a high-performance web framework for Python). In this tutorial, you'll Triton Inference Server is an open-source inference solution that standardizes model deployment and enables fast and scalable
Substratus.ai - Deploying and finetuning LLMs intro and demo AI Engineer Paris 2025 → Traffic is spiking to your ML application. Your autoscaler kicks in. llm-d Demo: Deploy Large Language Models on Kubernetes with Helm and Trace a Request
Onyx as an AI Chat Platform Tools like Langchain ( help you build applications on top of large
In this video we will step through deploying a LLM model production. In this example we will be using the Dolly LLM model from Langchain and PGVector - Retrieval Augmented Generation for LLM Question-Answering MLflow 3.0 Tutorial: The Ultimate Guide to LLM Tracking & AI Pipelines 🚀 | #mlflow #llmops #ai
Fine-tuning LLMs with PEFT and LoRA Quickstart — vLLM
A Quick Start. Introduction to vLLM | by Okan Yenigün | Towards Dev How-to Install vLLM and Serve AI Models Locally – Step by Step Easy Guide
MLC LLM: Enabling LLMs To Be Deployed Across Multiple Devices Deploying vLLM: a Step-by-Step Guide Learn how to build robust, type-safe AI agents in minutes with Pydantic AI in this step-by-step tutorial! I will create a fully functional
What is LangChain? Where does it fit with LLMs like ChatGPT and Cohere? #shorts Get started with LangGraph quickly & Learn Why its becoming one of the most popular agentic frameworks. Channel: Meta's New AI 'Tool LLM' Outperforms Every AI So Far!
Onyx provide a Gen AI Chat interface that can connect up to any LLM provider including local models like Ollama, VLLM and Today we learn about vLLM, a Python library that allows for easy and fast deployment and inference of LLMs. Learn how to easily install vLLM and locally serve powerful AI models on your own GPU! Buy Me a Coffee to support the
Using LangChain Output Parsers to get what you want out of LLMs Quickstart: Configure and deploy a vLLM server using Neuron Deep mlflow #mlflow3 #llm #llmops #mlops #aitools #machinelearning #datascience #python #tutorial #genai #llmtracking Join this
This guide will help you quickly get started with vLLM to perform: Prerequisites, Installation, If you are using NVIDIA GPUs, you can install vLLM using pip I want to run inference of a [specific model](put link here). I don't know how to integrate it with vllm. #llm-d: Dissecting the Kubernetes-Native AI Inference Architecture with vLLM & Gateway
OutParsers Colab: In this video I go through what outparsers are and how to use them in LangChain to Vllm Vs Triton | Which Open Source Library is BETTER in 2025? Dive into the world of Vllm and Triton as we put these two Getting started with vLLM · Installing vLLM · Checking your installation · Starting the vLLM server. Setting the dtype · Making requests. Using the
LoRA Colab : Blog Post: Welcome to our introduction to VLLM! In this video, we'll explore what VLLM is, its key features, and how it can help streamline
Pydantic AI in 10 Minutes | Practical QuickStart for Beginners Getting Started with NVIDIA Triton Inference Server Vast.ai Quickstart Guide (2025 Update) – Run AI Models on Cloud GPUs
vLLM can be deployed as a server that implements the OpenAI API protocol. This allows vLLM to be used as a drop-in replacement for applications using OpenAI API In this video, we review OpenLLM, and I show you how to install and use it. OpenLLM makes building on top of open-source
vLLM: A Beginner's Guide to Understanding and Using vLLM Let's see how to use AutoGEN without incurring the cost of OpenAI API. Discover, download, and run local LLMs. We have one
LangChain in Production - Microservice Architecture (incl. FastAPI and Docker) Quickstart - vLLM So you've learned how to prototype with Large Language Models (LLMs), but what's next? Supercharge your generative AI dev
Vector Databases simply explained. Learn what vector databases and vector embeddings are and how they work. Then I'll go In this tutorial, I'll walk you through the process of building an API for Large Language Models (LLMs) inference using Rust. You'll
In recent years, there has been remarkable progress in generative artificial intelligence (AI) and large language models (LLMs), Introduction to the Prometheus Monitoring System | Key Concepts and Features