From 49bdd1d7d1897d23d9b856b2186bf52b2d3635d8 Mon Sep 17 00:00:00 2001 From: GitLab CI Date: Thu, 11 Dec 2025 20:20:28 +0000 Subject: [PATCH] chore: Regenerate all playbooks --- README.md | 2 +- nvidia/comfy-ui/README.md | 4 ++-- nvidia/connect-to-your-spark/README.md | 2 ++ nvidia/connect-two-sparks/README.md | 3 +++ nvidia/cuda-x-data-science/README.md | 2 ++ nvidia/flux-finetuning/README.md | 2 ++ nvidia/jax/README.md | 2 ++ nvidia/llama-factory/README.md | 2 ++ nvidia/multi-modal-inference/README.md | 3 +++ nvidia/nccl/README.md | 8 +++++--- nvidia/nemo-fine-tune/README.md | 2 ++ nvidia/ollama/README.md | 9 ++++++--- nvidia/open-webui/README.md | 2 ++ nvidia/pytorch-fine-tune/README.md | 2 ++ nvidia/rag-ai-workbench/README.md | 2 +- nvidia/speculative-decoding/README.md | 2 ++ nvidia/tailscale/README.md | 2 +- nvidia/trt-llm/README.md | 4 +++- nvidia/unsloth/README.md | 3 +++ nvidia/vibe-coding/README.md | 2 ++ nvidia/vllm/README.md | 6 ++++-- nvidia/vss/README.md | 3 +++ 22 files changed, 55 insertions(+), 14 deletions(-) diff --git a/README.md b/README.md index c13d1ab..30b0bfc 100644 --- a/README.md +++ b/README.md @@ -46,7 +46,7 @@ Each playbook includes prerequisites, step-by-step instructions, troubleshooting - [Text to Knowledge Graph](nvidia/txt2kg/) - [Unsloth on DGX Spark](nvidia/unsloth/) - [Vibe Coding in VS Code](nvidia/vibe-coding/) -- [Install and Use vLLM for Inference](nvidia/vllm/) +- [vLLM for Inference](nvidia/vllm/) - [VS Code](nvidia/vscode/) - [Build a Video Search and Summarization (VSS) Agent](nvidia/vss/) diff --git a/nvidia/comfy-ui/README.md b/nvidia/comfy-ui/README.md index 1b6fde9..d2b9fa2 100644 --- a/nvidia/comfy-ui/README.md +++ b/nvidia/comfy-ui/README.md @@ -93,13 +93,13 @@ Verify the virtual environment is active by checking the command prompt shows `( ## Step 3. Install PyTorch with CUDA support -Install PyTorch with CUDA 12.9 support. +Install PyTorch with CUDA 13.0 support. ```bash pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu130 ``` -This installation targets CUDA 12.9 compatibility with Blackwell architecture GPUs. +This installation targets CUDA 13.0 compatibility with Blackwell architecture GPUs. ## Step 4. Clone ComfyUI repository diff --git a/nvidia/connect-to-your-spark/README.md b/nvidia/connect-to-your-spark/README.md index 74e3dc2..d050e14 100644 --- a/nvidia/connect-to-your-spark/README.md +++ b/nvidia/connect-to-your-spark/README.md @@ -67,6 +67,8 @@ applications, and manage your DGX Spark remotely from your laptop. - **Time estimate:** 5-10 minutes - **Risk level:** Low - SSH setup involves credential configuration but no system-level changes to the DGX Spark device - **Rollback:** SSH key removal can be done by editing `~/.ssh/authorized_keys` on your DGX Spark. +- **Last Updated:** 10/28/2025 + * Minor copyedits ## Connect with NVIDIA Sync diff --git a/nvidia/connect-two-sparks/README.md b/nvidia/connect-two-sparks/README.md index ecff809..7f3cf36 100644 --- a/nvidia/connect-two-sparks/README.md +++ b/nvidia/connect-two-sparks/README.md @@ -52,6 +52,9 @@ All required files for this playbook can be found [here on GitHub](https://githu - **Rollback:** Network changes can be reversed by removing netplan configs or IP assignments +- **Last Updated:** 11/24/2025 + * Minor copyedits + ## Run on Two Sparks ## Step 1. Ensure Same Username on Both Systems diff --git a/nvidia/cuda-x-data-science/README.md b/nvidia/cuda-x-data-science/README.md index 8d521e1..15f42cd 100644 --- a/nvidia/cuda-x-data-science/README.md +++ b/nvidia/cuda-x-data-science/README.md @@ -34,6 +34,8 @@ You will accelerate popular machine learning algorithms and data analytics opera * Data download slowness or failure due to network issues * Kaggle API generation failure requiring retries * **Rollback:** No permanent system changes made during normal usage. +* **Last Updated:** 11/07/2025 + * Minor copyedits ## Instructions diff --git a/nvidia/flux-finetuning/README.md b/nvidia/flux-finetuning/README.md index 28350c5..e028bdf 100644 --- a/nvidia/flux-finetuning/README.md +++ b/nvidia/flux-finetuning/README.md @@ -47,6 +47,8 @@ The setup includes: * Docker permission issues may require user group changes and session restart * The recipe would require hyperparameter tuning and a high-quality dataset for the best results * **Rollback**: Stop and remove Docker containers, delete downloaded models if needed. +* **Last Updated:** 11/07/2025 + * Minor copyedits ## Instructions diff --git a/nvidia/jax/README.md b/nvidia/jax/README.md index 62cef41..54d14fb 100644 --- a/nvidia/jax/README.md +++ b/nvidia/jax/README.md @@ -65,6 +65,8 @@ All required assets can be found [here on GitHub](https://github.com/NVIDIA/dgx- * Package dependency conflicts in Python environment * Performance validation may require architecture-specific optimizations * **Rollback:** Container environments provide isolation; remove containers and restart to reset state. +* **Last Updated:** 11/07/2025 + * Minor copyedits ## Instructions diff --git a/nvidia/llama-factory/README.md b/nvidia/llama-factory/README.md index c77724f..3a2643b 100644 --- a/nvidia/llama-factory/README.md +++ b/nvidia/llama-factory/README.md @@ -67,6 +67,8 @@ model adaptation for specialized domains while leveraging hardware-specific opti * **Duration:** 30-60 minutes for initial setup, 1-7 hours for training depending on model size and dataset. * **Risks:** Model downloads require significant bandwidth and storage. Training may consume substantial GPU memory and require parameter tuning for hardware constraints. * **Rollback:** Remove Docker containers and cloned repositories. Training checkpoints are saved locally and can be deleted to reclaim storage space. +* **Last Updated:** 10/12/2025 + * First publication ## Instructions diff --git a/nvidia/multi-modal-inference/README.md b/nvidia/multi-modal-inference/README.md index 0942553..f0d1f24 100644 --- a/nvidia/multi-modal-inference/README.md +++ b/nvidia/multi-modal-inference/README.md @@ -65,6 +65,9 @@ All necessary files can be found in the TensorRT repository [here on GitHub](htt - Remove downloaded models from HuggingFace cache - Then exit the container environment +* **Last Updated:** 10/12/2025 + * First publication + ## Instructions ## Step 1. Launch the TensorRT container environment diff --git a/nvidia/nccl/README.md b/nvidia/nccl/README.md index 6cbacb9..3dbf90a 100644 --- a/nvidia/nccl/README.md +++ b/nvidia/nccl/README.md @@ -41,9 +41,11 @@ and proper GPU topology detection. ## Time & risk -- **Duration**: 30 minutes for setup and validation -- **Risk level**: Medium - involves network configuration changes -- **Rollback**: The NCCL & NCCL Tests repositories can be deleted from DGX Spark +* **Duration**: 30 minutes for setup and validation +* **Risk level**: Medium - involves network configuration changes +* **Rollback**: The NCCL & NCCL Tests repositories can be deleted from DGX Spark +* **Last Updated:** 10/12/2025 + * First publication ## Run on two Sparks diff --git a/nvidia/nemo-fine-tune/README.md b/nvidia/nemo-fine-tune/README.md index cc29e59..3be0603 100644 --- a/nvidia/nemo-fine-tune/README.md +++ b/nvidia/nemo-fine-tune/README.md @@ -47,6 +47,8 @@ All necessary files for the playbook can be found [here on GitHub](https://githu * **Duration:** 45-90 minutes for complete setup and initial model fine-tuning * **Risks:** Model downloads can be large (several GB), ARM64 package compatibility issues may require troubleshooting, distributed training setup complexity increases with multi-node configurations * **Rollback:** Virtual environments can be completely removed; no system-level changes are made to the host system beyond package installations. +* **Last Updated:** 10/22/2025 + * Minor copyedits ## Instructions diff --git a/nvidia/ollama/README.md b/nvidia/ollama/README.md index dfd2939..561b813 100644 --- a/nvidia/ollama/README.md +++ b/nvidia/ollama/README.md @@ -44,13 +44,16 @@ the powerful GPU capabilities of your Spark device without complex network confi ## Time & risk -**Duration**: 10-15 minutes for initial setup, 2-3 minutes for model download (varies by model size) +* **Duration**: 10-15 minutes for initial setup, 2-3 minutes for model download (varies by model size) -**Risk level**: Low - No system-level changes, easily reversible by stopping the custom app +* **Risk level**: Low - No system-level changes, easily reversible by stopping the custom app -**Rollback**: Stop the custom app in NVIDIA Sync and uninstall Ollama with standard package +* **Rollback**: Stop the custom app in NVIDIA Sync and uninstall Ollama with standard package removal if needed +* **Last Updated:** 10/12/2025 + * First publication + ## Instructions ## Step 1. Verify Ollama installation status diff --git a/nvidia/open-webui/README.md b/nvidia/open-webui/README.md index bd61bd7..935d7bc 100644 --- a/nvidia/open-webui/README.md +++ b/nvidia/open-webui/README.md @@ -38,6 +38,8 @@ You will have a fully functional Open WebUI installation running on your DGX Spa * **Risks**: * Docker permission issues may require user group changes and session restart * Large model downloads may take significant time depending on network speed +* **Last Updated:** 10/28/2025 + * Minor copyedits ## Set up Open WebUI on Remote Spark with NVIDIA Sync diff --git a/nvidia/pytorch-fine-tune/README.md b/nvidia/pytorch-fine-tune/README.md index 9f6081b..150450a 100644 --- a/nvidia/pytorch-fine-tune/README.md +++ b/nvidia/pytorch-fine-tune/README.md @@ -51,6 +51,8 @@ ALl files required for fine-tuning are included in the folder in [the GitHub rep * **Time estimate:** 30-45 mins for setup and runing fine-tuning. Fine-tuning run time varies depending on model size * **Risks:** Model downloads can be large (several GB), ARM64 package compatibility issues may require troubleshooting. +* **Last Updated:** 11/07/2025 + * Fix broken commands to access files from GitHub ## Instructions diff --git a/nvidia/rag-ai-workbench/README.md b/nvidia/rag-ai-workbench/README.md index b9f9200..f62d9a6 100644 --- a/nvidia/rag-ai-workbench/README.md +++ b/nvidia/rag-ai-workbench/README.md @@ -58,7 +58,7 @@ architectures. * **Estimated time:** 30-45 minutes (including AI Workbench installation if needed) * **Risk level:** Low - Uses pre-built containers and established APIs * **Rollback:** Simply delete the cloned project from AI Workbench to remove all components. No system changes are made outside the AI Workbench environment. -* **Last Updated:** 11/21/2025 +* **Last Updated:** 10/28/2025 * Minor copyedits ## Instructions diff --git a/nvidia/speculative-decoding/README.md b/nvidia/speculative-decoding/README.md index b06969d..8030df6 100644 --- a/nvidia/speculative-decoding/README.md +++ b/nvidia/speculative-decoding/README.md @@ -55,6 +55,8 @@ These examples demonstrate how to accelerate large language model inference whil * **Duration:** 10-20 minutes for setup, additional time for model downloads (varies by network speed) * **Risks:** GPU memory exhaustion with large models, container registry access issues, network timeouts during downloads * **Rollback:** Stop Docker containers and optionally clean up downloaded model cache. +* **Last Updated:** 10/12/2025 + * First publication ## Instructions diff --git a/nvidia/tailscale/README.md b/nvidia/tailscale/README.md index 386761d..5d32bd1 100644 --- a/nvidia/tailscale/README.md +++ b/nvidia/tailscale/README.md @@ -73,7 +73,7 @@ all traffic automatically encrypted and NAT traversal handled transparently. * Network connectivity issues during initial setup * Authentication provider service dependencies * **Rollback**: Tailscale can be completely removed with `sudo apt remove tailscale` and all network routing automatically reverts to default settings. -* **Last Updated:** 11/21/2025 +* **Last Updated:** 11/07/2025 * Minor copyedits ## Instructions diff --git a/nvidia/trt-llm/README.md b/nvidia/trt-llm/README.md index 9432296..146b51b 100644 --- a/nvidia/trt-llm/README.md +++ b/nvidia/trt-llm/README.md @@ -1,6 +1,6 @@ # TRT LLM for Inference -> Install and configure TRT LLM to run on a single Spark or on two Sparks +> Install and use TensorRT-LLM on DGX Spark Sparks ## Table of Contents @@ -117,6 +117,8 @@ Reminder: not all model architectures are supported for NVFP4 quantization. * **Duration**: 45-60 minutes for setup and API server deployment * **Risk level**: Medium - container pulls and model downloads may fail due to network issues * **Rollback**: Stop inference servers and remove downloaded models to free resources. +* **Last Updated:** 10/18/2025 + * Fix broken links ## Single Spark diff --git a/nvidia/unsloth/README.md b/nvidia/unsloth/README.md index f62e1aa..0dfc457 100644 --- a/nvidia/unsloth/README.md +++ b/nvidia/unsloth/README.md @@ -55,6 +55,9 @@ The Python test script can be found [here on GitHub](https://github.com/NVIDIA/d * CUDA toolkit configuration issues may prevent kernel compilation * Memory constraints on smaller models require batch size adjustments * **Rollback**: Uninstall packages with `pip uninstall unsloth torch torchvision`. +* **Last Updated:** 11/07/2025 + * Add required python dependencies + * Fix broken commands to access files on GitHub ## Instructions diff --git a/nvidia/vibe-coding/README.md b/nvidia/vibe-coding/README.md index d8d4d01..f85cb9a 100644 --- a/nvidia/vibe-coding/README.md +++ b/nvidia/vibe-coding/README.md @@ -43,6 +43,8 @@ You'll have a fully configured DGX Spark system capable of: * **Duration:** About 30 minutes * **Risks:** Data download slowness or failure due to network issues * **Rollback:** No permanent system changes made during normal usage. +* **Last Updated:** 10/21/2025 + * First publication ## Instructions diff --git a/nvidia/vllm/README.md b/nvidia/vllm/README.md index e259d21..1cd6276 100644 --- a/nvidia/vllm/README.md +++ b/nvidia/vllm/README.md @@ -1,6 +1,6 @@ -# Install and Use vLLM for Inference +# vLLM for Inference -> Use a container or build vLLM from source for Spark +> Install and use vLLM on DGX Spark ## Table of Contents @@ -52,6 +52,8 @@ support for ARM64. * **Duration:** 30 minutes for Docker approach * **Risks:** Container registry access requires internal credentials * **Rollback:** Container approach is non-destructive. +* **Last Updated:** 10/18/2025 + * Minor copyedits ## Instructions diff --git a/nvidia/vss/README.md b/nvidia/vss/README.md index 5679cd7..cfb9c14 100644 --- a/nvidia/vss/README.md +++ b/nvidia/vss/README.md @@ -52,6 +52,9 @@ You will deploy NVIDIA's VSS AI Blueprint on NVIDIA Spark hardware with Blackwel * Network configuration conflicts if shared network already exists * Remote API endpoints may have rate limits or connectivity issues (hybrid deployment) * **Rollback:** Stop all containers with `docker compose down`, remove shared network with `docker network rm vss-shared-network`, and clean up temporary media directories. +* **Last Updated:** 10/18/2025 + * Update required OS and Driver versions + * Add instructions to fully local VSS deployment ## Instructions