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GPTQ Quantization Guide

Orchestra-Research/AI-Research-SKILLs

GPTQ enables post-training 4-bit quantization for large LLMs, delivering up to 4× memory reduction and 3-4× faster inference with under 2% perplexity loss on consumer GPUs through AutoGPTQ, PEFT, and Transformer integrations.

GPU Resource Optimizer

gpu-resource-optimizer

jeremylongshore/claude-code-plugins-plus-skills

Automates GPU resource optimization for ML deployments by guiding best practices, generating production-ready configurations, and validating setups for model serving, MLOps pipelines, and monitoring.

Gradient Clipping Helper

gradient-clipping-helper

jeremylongshore/claude-code-plugins-plus-skills

Gradient Clipping Helper automates ML training work by guiding gradient clipping workflows, generating production-ready code and configs, and validating outputs for PyTorch, TensorFlow, and related pipelines.

Groq Chat, Tools, and Structured Output

groq-core-workflow-a

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide to implementing advanced LLM patterns using the Groq API. This workflow demonstrates how to handle chat completions, robust tool/function calling for integrating external services (like weather or search), and enforcing structured data output using JSON mode and strict schemas. Ideal for building real-time, production-grade AI features.

Groq Multimodal Workflow: Audio, Vision, TTS

groq-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive workflow solution for Groq, enabling powerful multimodal tasks beyond simple chat completions. It supports ultra-fast audio transcription (Whisper), detailed image understanding using vision models, and professional text-to-speech generation. Use this for real-time content processing, multimedia analysis, and automated content creation.

Groq API Chat Completion Guide

groq-hello-world

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide to using Groq's high-speed LPU for chat completion. This resource provides code examples in TypeScript and Python, covering basic chat interactions, streaming responses, and advanced multimodal features. Ideal for developers building high-performance, low-latency AI applications using the Groq API.

Groq Production Architecture Design

groq-reference-architecture

jeremylongshore/claude-code-plugins-plus-skills

This guide details a production-ready reference architecture for applications built on Groq's LPU inference API. It covers sophisticated model routing based on latency, quality, or cost needs, implementing streaming pipelines, and establishing robust multi-provider fallback chains (e.g., Groq primary to OpenAI backup). Ideal for designing and reviewing complex, resilient LLM systems.

GroqCloud Automation Suite

groqcloud-automation

ComposioHQ/awesome-claude-skills

GroqCloud Automation orchestrates high-performance GroqCloud APIs through Composio, covering inference, chat completions, audio translation, and TTS voice selection for production workflows.

GRPO RL Fine-Tuning

grpo-rl-training

Orchestra-Research/AI-Research-SKILLs

Provides expert guidance for GRPO training with TRL, covering dataset prep, reward engineering, structured outputs, and multi-objective alignment when preference pairs are scarce.

HeyGen Video Automation

heygen-automation

ComposioHQ/awesome-claude-skills

Automate AI video creation workflows via the HeyGen-Composio MCP integration to browse avatars/templates, populate variables, generate videos, check processing status, and fetch shareable URLs.

Half-Quadratic Quantization

hqq-quantization

Orchestra-Research/AI-Research-SKILLs

Provides calibration-free weight quantization for LLMs down to 1-bit precision with multiple optimized backends, ideal for fast deployments with vLLM/HuggingFace and LoRA/PEFT fine-tuning without collecting calibration data.

Managing Hugging Face Models and Data

hugging-face-cli

sickn33/antigravity-awesome-skills

The official Hugging Face Hub CLI (`hf`) is a comprehensive command-line tool for managing all types of resources on the Hugging Face Hub. Use it to download, upload, synchronize, and manage models, datasets, Spaces, and cloud buckets. It facilitates secure authentication, local cache management, and complex data operations, making it essential for ML workflows.

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