data-labeling
claudeData labeling: annotation guidelines, platforms, inter-annotator agreement, active learning, weak supervision, and label error detection.
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claude
gpu-optimization
GPU optimization: profiling, memory management, torch.compile, Flash Attention, Triton kernels, and quantization.
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Plugin gpu-optimization from marketplace libre-mlops in HermeticOrmus/LibreMLOps-Claude-Code. Commands read from the repo's manifest — 1 month ago.
What it installs
Skills (1)
gpu-optimization-patternsGPU optimization patterns with code: memory profiling and budgeting, torch.compile modes, torch.profiler bottleneck analysis, BF16 and FP16 mixed precision, 4-bit quantization with bitsandbytes, and DataLoader tuning. Use when a GPU workload is slow or runs out of memory.
Slash commands (1)
/gpu-optimization:gpu-optimizeProfile a GPU workload, quantize it with bitsandbytes, GPTQ, or AWQ, apply torch.compile, or benchmark throughput before and after.
Subagents (1)
gpu-optimizerUse this agent when a deep learning workload is slow, memory-bound, or too expensive on GPU. It profiles first (NVIDIA Nsight, torch.profiler), then applies CUDA memory management, torch.compile, Flash Attention, Triton kernels, or GPTQ, AWQ, and bitsandbytes quantization, and measures after every c
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