Search results

• 1 HR

  TRT LLM for Inference

  Install and use TensorRT-LLM on DGX Spark

  Playbook
• Intermediate30 MIN

  Deploy NVIDIA NIM for LLM Inference

  Prebuilt, GPU-optimized model containers with a ready-to-use HTTP endpoint

  Playbook
• Intermediate30 MIN

  Run Hermes Agent with a Local LLM

  Chat from the terminal against local vLLM with the self-improving Nous Research agent (Telegram optional)

  Playbook
• Intermediate30 MIN

  Run NemoClaw with a Local LLM

  Build a local AI assistant in an OpenShell sandbox with vLLM inference and optional Telegram

  Playbook
• Intermediate30 MIN

  Run OpenClaw with a Local LLM

  Install a local-first AI agent and connect it to a private OpenAI-compatible model endpoint

  Playbook
• Intermediate30 MIN

  Serve LLMs with vLLM

  High-throughput serving for 30+ models, with continuous batching and an OpenAI-compatible API

  Playbook
• Intermediate30 MIN

  Serve LLMs with LM Studio

  Local models reachable from your own machine's tools over an encrypted link

  Playbook
• Beginner6 MIN

  Run Local LLMs

  Chat, agents, coding, and document Q&A with Ollama, LM Studio, and AnythingLLM on your hardware

  Playbook
• Intermediate30 MIN

  Serve LLMs with SGLang

  High-throughput serving with RadixAttention, structured output, and an OpenAI-compatible API

  Playbook
• Advanced60 MIN

  Run LLMs on Your NVIDIA Device

  Choose a model and spin it up locally on your NVIDIA device

  Playbook
• Intermediate60 MIN

  Fine-Tune LLMs with LLaMA Factory

  One interface for supervised, RLHF, and parameter-efficient training

  Playbook
• Intermediate8 MIN

  Fine-Tune Specialized LLMs with Unsloth

  LoRA, full training, and RL paths plus Nemotron open models

  Playbook
• Beginner15 MIN

  Chat with LLMs Using Open WebUI and Ollama

  A self-hosted browser interface with models running locally on your GPU

  Playbook
• Intermediate60 MIN

  Quantize Models to NVFP4 with NVIDIA Model Optimizer

  Cut memory ~3.5× vs FP16 while keeping accuracy close to FP8, then validate with an OpenAI-compatible endpoint

  Playbook
• 20 MIN

  Live VLM WebUI

  Real-time Vision Language Model interaction with webcam streaming

  Playbook
• 60 MIN

  cuTile Kernels

  Run cuTile kernel benchmarks, FMHA implementation, and LLM inference on DGX Spark and B300

  Playbook
• 30 MIN

  LM Studio on DGX Spark

  Deploy LM Studio and serve LLMs on a Spark device; use LM Link to access models remotely.

  Playbook
• 5 MIN

  How to Get Started With Large Language Models on NVIDIA RTX PCs

  Learn about using LLMs locally on PCs and workstations with Ollama, AnythingLLM, and LM Studio.

  Playbook
• 1 HR

  Vision-Language Model Fine-tuning

  Fine-tune Vision-Language Models for image and video understanding tasks using Qwen2.5-VL and InternVL3

  Playbook
• Intermediate2 HOURS

  Fine-Tune Vision Language Models

  Image and video understanding adapted to your own specialized tasks

  Playbook
• Intermediate30 MIN

  Stream Real-Time Video to a Vision Language Model

  A webcam-based testbed for comparing VLMs across backends

  Playbook
• Intermediate30 MIN

  Build Knowledge Graphs with txt2kg

  Extract triples with Ollama or vLLM, store them in a graph database, and explore them in a GPU-accelerated web UI

  Playbook
• 30 MIN

  Secure AI Agents with OpenShell

  Isolate OpenClaw with kernel-level policies and route inference to a local model

  Playbook
• Intermediate13 MIN

  Build a Multi-GPU AI PC

  Homogeneous dual-GPU setups for llama.cpp tensor parallel and ComfyUI multi-GPU diffusion

  Playbook