Results for “ram-sizing”

8 skills

qdrant-vertical-scaling

Guides vertical scaling decisions for Qdrant vector databases, covering when to scale up, how to resize nodes in Qdrant Cloud or self-hosted deployments, RAM sizing formulas, and when to switch to horizontal scaling.

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nemo-mbridge-perf-memory-tuning

Reduces peak GPU memory in Megatron Bridge training by applying expandable segments, parallelism resizing, activation recompute, and CPU offloading constraints.

physical-ai-neural-reconstruction

Routes NuRec/Neural Reconstruction requests to the correct upstream NVIDIA skill (datasets, conversion, training, rendering, object harvesting, frame cleanup).

Estimates the memory required to load Safetensors or GGUF model weights for inference from the Hugging Face Hub, using HTTP Range requests without downloading weights.

jetson-optimize-memory

Reclaim DRAM on NVIDIA Jetson devices by disabling unused display, camera, and DMA subsystems across MB1 BCT, MB2 BCT, kernel reserved-memory, and SWIOTLB layers for headless or no-camera deployments.

qdrant-memory-usage-optimization

Diagnoses and reduces Qdrant memory usage by analyzing resident memory, page cache, and providing optimization techniques like quantization, on-disk storage, and async_scorer.

adobe-resize-photos-and-videos

Resize photos and videos to exact pixel dimensions, aspect ratios, or named sizes using Adobe tools.

huggingface-best

Queries Hugging Face benchmark leaderboards to find the best AI models for a task, filters by device constraints, and returns a ranked comparison table with scores.