Plugins
11 plugins@nickgallick
Perlantir Fleet
Perlantir Fleet from nickgallick/perlantir-fleet.
34 skills · plugin
curated
Prepare Performance Review
Gather work evidence, analyze contributions, and draft a performance review.
3 skills · plugin
curated
Create Customer Persona
Create a customer persona by researching, synthesizing, and documenting user characteristics and behaviors.
3 skills · plugin
curated
Optimize Web Performance
Install this pack to optimize web performance by measuring and fixing Core Web Vitals.
9 skills · plugin
curated
Web Performance Audit and Optimize
Measure performance, identify bottlenecks, and apply fixes to improve Core Web Vitals.
9 skills · plugin
@nickgallick
Workspace
Workspace from nickgallick/perlantir-fleet.
20 skills · plugin
curated
Customer Discovery to Persona
Plan and conduct customer discovery interviews, summarize findings, and synthesize into actionable user personas.
5 skills · plugin
@flyfiref
Growth Companion
Growth Companion from FlyFireF/PersonalAgentAPP.
30 skills · plugin
curated
Web Performance Audit and Fix
Installs a pipeline to audit Core Web Vitals, analyze performance, and debug issues using DevTools.
10 skills · plugin
@nickgallick
Workspace Forge
Workspace Forge from nickgallick/perlantir-fleet.
13 skills · plugin
@nickgallick
Workspace Pixel
Workspace Pixel from nickgallick/perlantir-fleet.
11 skills · plugin
Results for “pe”
62 skillsPennylane
Train quantum circuits with automatic differentiation and build hybrid quantum-classical models using PennyLane, including VQE, QAOA, and integration with PyTorch, JAX, and TensorFlow.
3 · bundle
Tao Analyze Gaps Visual Changenet
Identifies the weakest samples per ground-truth label in NVIDIA TAO VCN Classify experiments by running a Docker container that performs threshold sweep, weakness scoring, and per-lighting expansion, then surfaces top-K weak samples for downstream augmentation or relabeling.
2.2k · bundle
Pufferlib
Train reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.
30.2k · bundle
Tao Train Reid
Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.
2.2k · bundle
Pennylane
Train quantum circuits like neural networks with automatic differentiation, device-independent programming, and integration with PyTorch or JAX.
30.2k · bundle
Fine Tuning Expert
Fine-tune LLMs using LoRA, QLoRA, and PEFT with Hugging Face, including dataset preparation, hyperparameter tuning, evaluation, and deployment.
10.4k · bundle
More results
03 Performance
Optimizes Dify workflows and plugins by restructuring graphs, reducing LLM token usage, tuning worker pools, and improving parallel processing.
34 · bundle
Julia Pro
Provides expert guidance on modern Julia 1.10+ development, covering performance optimization, multiple dispatch, tooling, testing, and production-ready practices.
42.4k
Hqq Quantization
Quantize large language models to 8/4/3/2/1-bit precision without calibration data, using multiple optimized backends and integrations with HuggingFace Transformers, vLLM, and PEFT/LoRA.
567 · bundle
Peft Fine Tuning
Fine-tune large language models by training less than 1% of parameters using LoRA, QLoRA, and 25+ adapter methods, enabling efficient adaptation on limited GPU memory.
2
Nemo Mbridge Perf Moe Comm Overlap
Optimizes MoE expert-parallel communication overlap in Megatron Bridge, covering dispatch/combine overlap, flex dispatcher backends, and expert wgrad scheduling.
2.2k · bundle
Geniml
Train unsupervised machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.
30.2k · bundle
Peft Fine Tuning
Fine-tune large language models by training less than 1% of parameters using LoRA, QLoRA, and 25+ adapter methods, enabling efficient adaptation on consumer GPUs.
10.4k · bundle
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.
2.2k · bundle
Bleurt
Evaluates the correlation between automatic text generation scores and human quality ratings, including robustness to domain and quality drift, using metrics like Kendall's Tau and Pearson correlation.
3
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.
2.2k · bundle
Feqa
Evaluates the faithfulness of abstractive summaries by generating questions from summary sentences and verifying if the answers can be extracted from the source document, reporting Pearson and Spearman correlations with human judgments.
3
Detecting Model Extraction Attacks
Detect model stealing, model inversion, and membership inference performed through inference-API abuse by monitoring query patterns, applying output perturbation, and red-teaming your own model's extractability.
24.6k · bundle
Algorithms
Implements and applies algorithms concepts, designs solutions using algorithmic principles, and optimizes performance for algorithm implementations.
1
Jetson LLM Benchmark
Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.
2.2k · bundle
Jax
High-performance numerical computing with JAX, covering functional transformations, Flax NNX, and best practices for ML research.
567 · bundle
Hqq Quantization
Quantize LLMs to 8/4/3/2/1-bit precision without calibration data, using multiple backends and HuggingFace/vLLM integration.
3 · bundle
Tensorboard
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard.
3 · bundle
Tensorboard
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance using TensorBoard.
10.4k · bundle
Gi Enhancer
Predicts enhancer activity in DNA sequences using the hosted Genomic Intelligence G0 DeepSTARR model, returning per-window activity scores.
17 · bundle
Aeon
Performs time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search using the aeon toolkit.
3 · bundle
Nemo Mbridge Perf Megatron Fsdp
Enables Megatron Fully Sharded Data Parallel in Megatron-Bridge with configuration overrides, code anchors, pitfalls, and verification steps.
2.2k · bundle
Modal Serverless Gpu
Run ML workloads on Modal's serverless GPU cloud platform with auto-scaling, pay-per-second pricing, and Python-native infrastructure.
10.4k · bundle
Rdkit
Provides guidance for using RDKit to read and write molecular structures, calculate descriptors, generate fingerprints, perform substructure searches, and handle chemical reactions.
253 · bundle
Modal
Deploy and serve AI/ML models on Modal's serverless cloud platform with on-demand GPUs, autoscaling containers, persistent storage, and scheduled jobs.
30.2k · bundle
Pyvene Interventions
Perform causal interventions on PyTorch models using pyvene's declarative framework for causal tracing, activation patching, and interchange intervention training.
10.4k · bundle
Geniml
Trains machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.
253 · 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.
2.2k · bundle
Cobrapy
Performs constraint-based metabolic modeling with COBRApy: FBA, FVA, gene knockouts, flux sampling, and SBML model handling for systems biology and metabolic engineering.
253 · bundle
Nemo Mbridge Perf Cpu Offloading
Configure and validate CPU offloading for Megatron Bridge training, including activation offloading and optimizer state offloading with HybridDeviceOptimizer.
2.2k · bundle
Sdr
Quantifies audio source separation quality by computing the signal-to-distortion ratio (SDR) between ground-truth and estimated stems, with per-stem and record-level averaging.
3