Packs
12 packs@galyarderlabs
Galyarder Framework
Galyarder Framework from galyarderlabs/galyarder-framework.
100 skills · pack
@b4san
.Roo
.Roo from B4san/AC-framework.
47 skills · pack
@alirezarezvani
Compliance Os
Compliance OS — meta-orchestrator for multi-framework compliance programs spanning 9 frameworks (ISO 27001, ISO 13485, ISO 42001, ISO 14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR). Framework selector, cross-framework control mapper, audit simulator, and consolidated evidence-pool generator (stdlib Python), plus 3 cs-* compliance agents and 3 /cs:* readiness commands.
9 skills · pack
curated
B2B Case Study
Research, write, and format a B2B case study using the STAR framework.
3 skills · pack
curated
Run Agent Evaluation
Sets up evaluation framework, runs benchmarks, and produces comparative analysis of agent performance.
9 skills · pack
@dotnet
Dotnet Upgrade
Skills for migrating and upgrading .NET projects across framework versions, language features, and compatibility targets.
6 skills · pack
curated
Write B2B Case Study
Write a compelling B2B case study using the STAR framework with research and data visualization.
3 skills · pack
@cjthompson
Textual
Reference skills for the Textual Python TUI framework — valid CSS properties and complete widget API with reactive attributes.
2 skills · pack
@phuryn
Execution
Execution and product management skills: PRDs, OKRs, roadmaps, sprints, pre-mortems, stakeholder maps, user stories, prioritization frameworks, and more.
16 skills · pack
curated
Product Strategy Canvas Pack
For product managers and strategists to define, analyze, and refine product strategy using complementary canvas frameworks.
3 skills · pack
curated
Backend Framework Patterns
For developers building production-grade backends with NestJS, Spring Boot, or Ktor, covering architecture patterns and best practices.
7 skills · pack
curated
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
Results for “framework”
11 skills
dotnet technology-selection
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI, Microsoft Agent Framework, GitHub Copilot SDK, ONNX Runtime, and OllamaSharp.
4k
antigravity cirq
Design, simulate, and run quantum circuits on quantum computers and simulators using Google's Cirq framework.
42.4k
qhjqhj00 mlflow
Track ML experiments, manage the model registry with versioning, deploy models, and reproduce experiments using MLflow's framework-agnostic platform.
3 · bundle
k-dense-ai qiskit
Build and execute quantum circuits on IBM Quantum hardware, simulators, and third-party providers using the Qiskit framework.
30.2k · bundle
antigravity ml-engineer
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks, including model serving, feature engineering, A/B testing, and monitoring.
42.4k
More results
orchestra-research miles-rl-training
Train large-scale MoE models with FP8/INT4 low-precision RL, speculative decoding, and train-inference alignment using the miles framework.
10.4k · bundle
orchestra-research 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
orchestra-research slime-rl-training
Post-train LLMs with reinforcement learning using the slime framework, which integrates Megatron-LM for training and SGLang for rollout generation.
10.4k · bundle
orchestra-research pytorch-lightning
Organizes PyTorch code with a Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks, and minimal boilerplate. Scales from laptop to supercomputer with the same code.
10.4k · bundle
lord1egypt slime-rl-training
Guides LLM post-training with RL using slime, a Megatron+SGLang framework for training GLM, Qwen, DeepSeek, and Llama models with GRPO, async, and multi-turn workflows.
2
qhjqhj00 latency
Measures inference latency of binarized, 8-bit, and 32-bit convolutional layers on edge devices to evaluate the efficiency and speedup of the Larq Compute Engine framework compared to standard implementations.
3