Results for “gpqa”

Quantize large language models to 4-bit with minimal accuracy loss using GPTQ, enabling deployment of 70B+ models on consumer GPUs with 4× memory reduction and 3-4× faster inference.

Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.

Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.

Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.

Configures GKE autoscaling with HPA, VPA, and Node Auto-Provisioning using golden path defaults for cost optimization.

Runs a comprehensive QA audit on Unity, Unreal, Godot, or web game projects, covering null references, missing assets, scene transitions, physics, input, save/load, localization, audio, and platform certification.

Screen products for FDA, EPA, USDA, CPSC, FCC, and other government agency requirements using AskRosetta. Use when checking regulatory compliance for US imports.

Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to "qa", "QA", "test this site", "find bugs", "test and fix", or "fix what's broken". Proactively suggest when the user says a feature is ready for testing or asks "does this work?". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary. For report-only mode, use /qa-only. (gstack) Voice triggers (speech-to-text aliases): "quality check", "test the app", "run QA".

Automates genome-wide association studies from genotype files to publication-ready results, running PLINK2 QC and REGENIE regression with Manhattan and QQ plots.

Quantize large language models to 4-bit precision using activation-aware weight quantization, reducing memory footprint and speeding up inference with minimal accuracy loss.

Expert en infrastructure GCP (GKE, Cloud Run, BigQuery, Pub/Sub, Firestore, Cloud Functions)

GPG (GNU Privacy Guard) encryption and signing reference. Covers key generation (Ed25519/RSA), export/import, keyservers, file encryption (symmetric + asymmetric), git commit signing, detached signatures, gpg-agent caching, SSH via GPG, and pass password manager.

Engineering privacy and data governance: PII detection, data flow mapping, consent patterns, GDPR/CCPA-compliant implementation, DPIA. Use when privacy-by-design is needed.

GPG (GNU Privacy Guard) encryption and signing reference. Covers key generation (Ed25519/RSA), export/import, keyservers, file encryption (symmetric + asymmetric), git commit signing, detached signatures, gpg-agent caching, SSH via GPG, and pass password manager.

Automate the generation and maintenance of unit, integration, and end-to-end tests, as well as test data generation and debugging. Use when writing tests for new features, maintaining existing tests after API/UI changes, generating synthetic test data, or debugging test failures. Essential for ensuring code quality and preventing regressions.

Extracts GraphQL API schemas through introspection attacks, identifies sensitive fields and mutations, and tests for query depth and complexity vulnerabilities.

QA cycling workflow - test, verify, fix, repeat until goal met

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

Aggregate cross-asset quality control for campaigns. Use when the user requests 'run QC', 'quality check campaign', 'review all assets', or 'generate QA report'.

Systematically QA test a web application and fix bugs found. (gstack)

Report-only QA testing. (gstack)

Systematically QA test a web application and fix bugs found. (gstack)

12 regulatory & QM agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, ISO 27001 ISMS, GDPR/DSGVO, risk management (ISO 14971), CAPA, document control, auditing. Python tools (stdlib-only).

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

Performs a comprehensive cross-artifact QA/QC review of a virtual team pipeline, checking completeness, consistency, security, and compliance, then issues an advisory verdict with quality, compliance, and sign-off reports.

Reviews all pipeline artifacts from a virtual software team and produces quality, compliance, and sign-off reports with an advisory release verdict.

Generate comprehensive test plans, manual test cases, regression test suites, and bug reports for QA engineers. Includes Figma MCP integration for design validation.

Simulates BGP hijacking attacks in isolated lab environments to test RPKI deployment, route origin validation, and BGP monitoring defenses against prefix hijacking and route leak attacks.

Maps the Salesforce CPQ managed-package object graph (SBQQ__ namespace) and explains when to use the CPQ Quote API for programmatic writes instead of direct DML.

Scans codebases for GDPR/DSGVO compliance issues, generates DPIA documentation, and tracks data subject rights requests with deadline management.

Use to audit QA coverage and scorecard health in a Rulebase workspace via the Rulebase MCP server. Trigger for "audit our QA coverage", "which agents or channels aren't being evaluated", "are our QA scores meaningful", "is our scorecard working", QA blind spots, score distribution or ceiling effects, and checking whether QA scores relate to SLA or complaint outcomes.

Performs free, open-source reverse engineering with Ghidra using headless or GUI modes, including decompilation, cross-references, and optional MCP workflows when IDA is unavailable.

Provides HIPAA-specific decision gates and guardrails for healthcare software, directing users to implementation and review skills for PHI handling, audit logging, and compliance.

Assess GraphQL API endpoints for introspection leaks, injection attacks, authorization flaws, and denial-of-service vulnerabilities during authorized security tests.

GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.