Tutorial - Introduction
Overview
Our tutorials are divided into categories roughly based on model modality, the type of data to be processed or generated.
Text (LLM)
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text-generation-webui
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Interact with a local AI assistant by running a LLM with oobabooga's text-generaton-webui
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Ollama
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Get started effortlessly deploying GGUF models for chat and web UI
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llamaspeak
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Talk live with Llama using Riva ASR/TTS, and chat about images with Llava!
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NanoLLM
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Optimized inferencing library for LLMs, multimodal agents, and speech.
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Small LLM (SLM)
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Deploy Small Language Models (SLM) with reduced memory usage and higher throughput.
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API Examples
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Learn how to write Python code for doing LLM inference using popular APIs.
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Text + Vision (VLM)
Give your locally running LLM an access to vision!
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LLaVA
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Different ways to run
LLaVa
vision/language model on Jetson for visual understanding.
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Live LLaVA
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Run multimodal models interactively on live video streams over a repeating set of prompts.
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NanoVLM
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Use mini vision/language models and the optimized multimodal pipeline for live streaming.
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Llama 3.2 Vision
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Run Meta's multimodal Llama-3.2-11B-Vision model on Orin with HuggingFace Transformers.
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EfficientVIT
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MIT Han Lab's
EfficientViT
, Multi-Scale Linear Attention for High-Resolution Dense Prediction
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NanoOWL
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OWL-ViT
optimized to run real-time on Jetson with NVIDIA TensorRT
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NanoSAM
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NanoSAM
, SAM model variant capable of running in real-time on Jetson
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SAM
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Meta's
SAM
, Segment Anything model
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TAM
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TAM
, Track-Anything model, is an interactive tool for video object tracking and segmentation
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Image Generation
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Flux + ComfyUI
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Set up and run the ComfyUI with Flux model for image generation on Jetson Orin.
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Stable Diffusion
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Run AUTOMATIC1111's
stable-diffusion-webui
to generate images from prompts
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SDXL
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Ensemble pipeline consisting of a base model and refiner with enhanced image generation.
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nerfstudio
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Experience neural reconstruction and rendering with nerfstudio and onboard training.
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Audio
RAG & Vector Database
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NanoDB
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Interactive demo to witness the impact of Vector Database that handles multimodal data
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LlamaIndex
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Realize RAG (Retrieval Augmented Generation) so that an LLM can work with your documents
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LlamaIndex
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Reference application for building your own local AI assistants using LLM, RAG, and VectorDB
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API Integrations
About NVIDIA Jetson
Note
We are mainly targeting Jetson Orin generation devices for deploying the latest LLMs and generative AI models.
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Jetson AGX Orin 64GB Developer Kit
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Jetson AGX Orin Developer Kit
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Jetson Orin Nano Developer Kit
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GPU
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2048-core NVIDIA Ampere architecture GPU with 64 Tensor Cores
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1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores
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RAM
(CPU+GPU)
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64GB
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32GB
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8GB
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Storage
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64GB eMMC (+ NVMe SSD)
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microSD card (+ NVMe SSD)
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