From ede88f5c222933ddba7d0d48b40c9295e38399ea Mon Sep 17 00:00:00 2001 From: GitHub Actions Date: Wed, 13 Nov 2024 18:52:35 +0000 Subject: [PATCH] Deployed d60ad91debaf6c7a922527a71382b709c93e38cd with mkdocs-material v9.5.44 and HTML post-processing --- 404.html | 11 +- agent_studio.html | 11 +- benchmarks.html | 11 +- community_articles.html | 11 +- getting-started.html | 11 +- hello_ai_world.html | 11 +- index.html | 11 +- initial_setup_jon.html | 11 +- lerobot.html | 17 +- llama_vlm.html | 11 +- nerf.html | 11 +- openvla.html | 11 +- research.html | 11 +- ros.html | 11 +- search/search_index.json | 2 +- site/tensorrt_llm.html | 2164 +++++++++++++++++++++++++++++ sitemap.xml.gz | Bin 127 -> 127 bytes tensorrt_llm.html | 1072 ++++++++++++++ tips_ram-optimization.html | 11 +- tips_ssd-docker.html | 11 +- try.html | 11 +- tutorial-intro.html | 11 +- tutorial_api-examples.html | 11 +- tutorial_audiocraft.html | 11 +- tutorial_comfyui_flux.html | 11 +- tutorial_distillation.html | 11 +- tutorial_efficientvit.html | 7 +- tutorial_gapi_microservices.html | 11 +- tutorial_gapi_workflows.html | 11 +- tutorial_holoscan.html | 11 +- tutorial_jetson-copilot.html | 11 +- tutorial_jps.html | 11 +- tutorial_live-llava.html | 11 +- tutorial_llamaindex.html | 11 +- tutorial_llamaspeak.html | 11 +- tutorial_llava.html | 11 +- tutorial_minigpt4.html | 11 +- tutorial_mmj.html | 11 +- tutorial_nano-llm.html | 13 +- tutorial_nano-vlm.html | 11 +- tutorial_nanodb.html | 11 +- tutorial_nanoowl.html | 7 +- tutorial_nanosam.html | 7 +- tutorial_ollama.html | 11 +- tutorial_sam.html | 7 +- tutorial_slm.html | 13 +- tutorial_stable-diffusion-xl.html | 11 +- tutorial_stable-diffusion.html | 11 +- tutorial_tam.html | 7 +- tutorial_text-generation.html | 11 +- tutorial_ultralytics.html | 11 +- tutorial_voicecraft.html | 11 +- tutorial_whisper.html | 11 +- vit/index.html | 11 +- vit/tutorial_efficientvit.html | 11 +- vit/tutorial_nanoowl.html | 11 +- vit/tutorial_nanosam.html | 11 +- vit/tutorial_sam.html | 11 +- vit/tutorial_tam.html | 11 +- 59 files changed, 3717 insertions(+), 116 deletions(-) create mode 100644 site/tensorrt_llm.html create mode 100644 tensorrt_llm.html diff --git a/404.html b/404.html index 814dc15d..57eb2c03 100644 --- a/404.html +++ b/404.html @@ -6,7 +6,7 @@ - + NVIDIA Jetson AI Lab @@ -254,6 +254,13 @@ +
  • + + + TensorRT-LLM 🆕 + + +
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  • - LeRobot 🆕 + LeRobot
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    Rapidly design and experiment with creating your own automation agents, personal assistants, and edge AI systems in an interactive sandbox for connecting multimodal LLMs, speech and vision transformers, vector databases, prompt templating, and function calling to live sensors and I/O. Optimized for deployment onboard Jetson with on-device compute, low-latency streaming, and unified memory.

    \u2022 Edge LLM inference with quantization and KV caching (NanoLLM) \u2022 Realtime vision/language models (ala Live Llava and Video VILA) \u2022 Speech recognition and synthesis (Whisper ASR, Piper TTS, Riva) \u2022 Multimodal vector database from NanoDB \u2022 Audio and video streaming (WebRTC, RTP, RTSP, V4L2) \u2022 Performance monitoring and profiling \u2022 Native bot-callable functions and agent tools \u2022 Extensible plugins with auto-generated UI controls \u2022 Save, load, and export pipeline presets \u2022 Native bot-callable functions and agent tools"},{"location":"agent_studio.html#running-agent-studio","title":"Running Agent Studio","text":"

    What you need

    1. One of the following Jetson devices:

      Jetson AGX Orin (64GB) Jetson AGX Orin (32GB) Jetson Orin NX (16GB) Jetson Orin Nano (8GB)

    2. Running one of the following versions of JetPack:

      JetPack 6 (L4T r36.x)

    3. Sufficient storage space (preferably with NVMe SSD).

      • 22GB for nano_llm container image
      • Space for models (>5GB)
    4. Clone and setup jetson-containers:

      git clone https://github.com/dusty-nv/jetson-containers\nbash jetson-containers/install.sh\n
    jetson-containers run --env HUGGINGFACE_TOKEN=hf_xyz123abc456 \\\n  $(autotag nano_llm) \\\n    python3 -m nano_llm.studio\n

    This will start the server running on your device. You can then navigate your browser to https://IP_ADDRESS:8050