Results for “customgpt”

Use for designing, auditing, or refactoring a GitHub Copilot customization system in Visual Studio Code across instructions, prompt files, Agent Skills, custom agents, hooks, MCP servers, and plugins. Do not use merely to author one already-selected artifact or configure unrelated VS Code settings.

Generates a complete Custom GPT knowledge package from the current workspace project, producing 20 markdown documentation files plus optimized custom instructions for a strategic consultant.

Generate GPT API request payloads. Use when building chat completions, embeddings, fine-tuning data, or estimating API costs.

Bootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit.

Create concise tldr summaries for GitHub Copilot customization files, MCP server documentation, or Copilot documentation from URLs or queries.

Provides GKE golden path configuration defaults, production readiness checklists, and cluster default patterns for designing and verifying GKE clusters.

Generates kernel-DT overlay fragments to enable 25G/10G/1G MGBE QSFP interfaces on Jetson Thor, verifying pinmux and integrating with the BSP customization workflow.

Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).

Use when the user asks Codex to directly generate images with gpt-image-2 using inherited OpenAI/Codex-compatible environment credentials or local GPT_IMAGE2_* overrides, including text-to-image, reference-image guided generation, ratios, resolution, quality, variants, and saved local image files; run the bundled Node CLI and keep URL/sk configuration private.

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.

Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).

Turn a private skill you built for your own stack into a clean public version anyone can install and customize, while preserving your personal copy untouched. Strips the company-specific wiring (connectors, CRM field names, proprietary scores, IDs, tuned thresholds, internal vocabulary) and abstracts it into a documented "Customize this for yourself" setup block, keeping the method intact. Trigger on "publish this skill", "make a public version of", "genericize this skill", "share-ready version of", "turn my skill into a community version", "add this to the Built GTM Skills page".

Instruction Tuning with GPT-4

Configure repository-specific guidance for GitHub Copilot by creating and structuring .github/copilot-instructions.md files.

Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).

Comprehensive guide to gpt. Master the concepts, implementation, best practices, and real-world applications of gpt in professional environments.

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.

Generates a single-file horizontal-scroll web PPT with WebGL backgrounds, section covers, data hero cards, and image grids in two visual styles: 'e-magazine × e-ink' or 'Swiss International Style'.

Privacy Policy Generator

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.

Generate complete Power Platform custom connectors with Model Context Protocol integration for Copilot Studio, including schema generation, validation, troubleshooting, and certification preparation.

Creates GKE clusters with golden path Autopilot defaults, supporting Standard and GPU workloads. Guides through project, region, and networking inputs, then provisions and verifies cluster settings.

Suggest relevant GitHub Copilot Custom Agents from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates and identifying outdated agents.

Scaffold, build, and refactor ChatGPT Apps SDK projects with a docs-first workflow, combining MCP servers and widget UIs.

Analyzes differences between two project versions to generate precise migration instructions for GitHub Copilot, enabling consistent code transformations during technology migrations, refactoring, or framework upgrades.

Bootstraps a BSP customization workspace for NVIDIA Jetson, including the Linux_for_Tegra overlay tracker, bsp_sources mono-tree, and Crosstool-NG toolchain.

Plans, configures, and manages GKE networking including private clusters, VPC-native configurations, Gateway API, DNS, ingress/egress, Dataplane V2, and IP planning.

Initialize a Git repository with an initial commit

Generates production-grade Kubernetes manifests including Deployments with probes and security contexts, Services, Ingress with TLS, HPA, PDB, NetworkPolicy, ConfigMaps, and Secrets, with optional Helm charts, Kustomize overlays, Istio mesh, and ArgoCD GitOps.

Elite UX/UI & Advanced GSAP Motion Engineer. Enforces Python-driven true randomization for layout variance, strict AIDA page structure, wide editorial typography (bans 6-line wraps), gapless bento grids, strict GSAP ScrollTriggers (pinning, stacking, scrubbing), inline micro-images, and massive section spacing.

Train and experiment with a minimal GPT implementation in ~300 lines of PyTorch, from character-level Shakespeare to GPT-2 scale.

Generates award-level UI with GSAP motion, bento grids, and Python-driven randomization for layout variety.

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.

Use after the user has authorized GPT Pro help; manage a prompt-plus-sources workspace, route through ChatGPT Projects when available, and audit returned reasoning.

Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).