Packs

8 packs

Comprehensive MSBuild and .NET build skills: failure diagnosis, performance optimization, code quality, and modernization.

18 skills · pack

Optimize GKE Costs

Analyzes current usage, recommends cost-saving measures, and applies optimizations to GKE workloads.

3 skills · pack

AI Search Optimization

Analyze and optimize content for AI Overviews, ChatGPT, and Perplexity using GEO techniques.

9 skills · pack

CRO Landing Page Optimization

Diagnose conversion issues, design high-converting page elements, and optimize forms to boost conversions.

9 skills · pack

SEO Audit to Optimization

Audit a website for SEO issues, analyze on-page elements, and implement fixes to improve organic performance.

9 skills · pack

Google Cloud Well-Architected

For architects evaluating Google Cloud workloads against the Well-Architected Framework pillars: reliability, cost optimization, and operational excellence.

6 skills · pack

Edge Delivery Services Content Ops

Content operations skills for AEM Edge Delivery Services: page auditing, SEO optimization, AI search (GEO), WCAG accessibility, bulk metadata, structured data, sitemap validation, and content diffing

12 skills · pack

@alirezarezvani

Multi-agent collaboration — spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any task that benefits from diverse solutions. 7 slash commands (/hub:init, /hub:spawn, /hub:status, /hub:eval, /hub:merge, /hub:board, /hub:run), agent templates, DAG-based orchestration, LLM judge mode, message board coordination.

8 skills · pack

Results for “optimization”

31 skills

orchestra-research

Provides expert guidance for fast fine-tuning with Unsloth, including LoRA/QLoRA optimization, with 2-5x faster training and 50-80% less memory usage.

10.4k · bundle

Solve single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including Pareto front analysis, constraint handling, and benchmarking on standard test problems.

Run automated hyperparameter optimization for NVIDIA TAO models using AutoMLRunner, supporting multiple search algorithms and experiment tracking.

Deploy and serve LLMs in production with vLLM, Ollama, TGI, and llama.cpp, including quantization and GPU optimization.

orchestra-research

Train language models with SimPO, a reference-free preference optimization method that outperforms DPO without needing a reference model.

10.4k · bundle

Manages the lifecycle of large language models in production, covering model versioning, prompt management, inference optimization, and cost control.

More results

Provides expert guidance on modern Julia 1.10+ development, covering performance optimization, multiple dispatch, tooling, testing, and production-ready practices.

orchestra-research

Provides expert guidance for distributed training with DeepSpeed, covering ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, and sparse attention.

10.4k · bundle

Trains language models with Direct Preference Optimization using preference pairs, covering DPOTrainer setup, dataset preparation, and beta tuning for stable preference learning without explicit reward models.

Trains LLMs with SimPO, a reference-free preference optimization method that outperforms DPO, using configurable hyperparameters and workflows for various models and tasks.

Runs an autonomous optimization loop that iteratively improves an artifact against an objective and evaluator using Hypothesis Tree Refinement, with subagent executors in isolated git worktrees.

Performs finite element analysis, computational fluid dynamics, thermal analysis, modal analysis, and design optimization for validating designs against physical loads and predicting product behavior.

Solves single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including constraint handling, Pareto front analysis, and benchmark problems.

Solve single and multi-objective optimization problems using NSGA-II/III, MOEA/D, and other evolutionary algorithms with customizable operators, constraint handling, and benchmark problems.

30.2k · bundle

Implements and applies algorithms concepts, designs solutions using algorithmic principles, and optimizes performance for algorithm implementations.

deepstream-profile-pipeline

Profile a DeepStream pipeline with Nsight Systems and derive its configs from the measurement.

Guides machine learning development with experiment tracking, hyperparameter optimization, model registry, and MLOps pipeline integration.

Design, simulate, and run quantum circuits on Google Quantum AI hardware and partner backends using Cirq.

30.2k · bundle

Formalizes narrative technical documents into structured mathematical problem specifications with variables, constraints, objectives, and uncertainty, citing evidence and flagging missing information.

Analyzes raw genomic data (FASTQ/VCF) to generate non-medical wellness, longevity, and pharmacogenomic optimization protocols while keeping DNA processing local and private.

Optimizes Dify workflows and plugins by restructuring graphs, reducing LLM token usage, tuning worker pools, and improving parallel processing.

Guides users through participating in the SOMA decentralized training network, covering data submission, model training, reward claiming, and strategic optimization.

orchestra-research

skypilot-multi-cloud-orchestration

Run ML training and batch jobs across multiple clouds with automatic cost optimization, spot instance recovery, and unified orchestration.

10.4k · bundle

jetson-speculative-decoding

Reduce per-token latency on Jetson vLLM servers by appending speculative decoding configuration, with guidance on when to enable and how to benchmark the improvement.

cuopt-multi-objective-exploration

Trace and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).

Selects the right Gemma model for a task, recommends deployment tooling (Gradio, Transformers.js, Vertex AI, MLX), and applies optimizations like MTP and QAT.

nemotron-customize

Plan, configure, and chain Nemotron model customization steps into single-step or multi-step pipelines for curation, translation, fine-tuning, RL alignment, benchmarking, checkpoint conversion, optimization, and evaluation.

nemo-mbridge-perf-cuda-graphs

Validate and use CUDA graph capture in Megatron Bridge, including local full-iteration graphs and Transformer Engine scoped graphs for attention, MLP, and MoE modules.

orchestra-research

optimizing-attention-flash

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

10.4k · bundle

Measures the trade-off between computation time and energy consumption in mobile edge computing by computing a weighted sum of the two objectives, given system configuration parameters and per-user task characteristics.

orchestra-research

quantizing-models-bitsandbytes

Quantize LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss using bitsandbytes. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers.

10.4k · bundle