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Managed HuggingFace Jobs

hugging-face-jobs

sickn33/antigravity-awesome-skills

Deploy and monitor Python workloads on Hugging Face Jobs, leveraging managed CPUs, GPUs, TPUs, secure secrets, and Hub persistence without local setup; ideal for data processing, batch inference, experiments, scheduled automation, and training.

Instructor Structured Outputs

Orchestra-Research/AI-Research-SKILLs

Instructor turns LLM responses into validated structured data with Pydantic schemas, automatic retries on failed extractions, complex JSON parsing, and streaming partial results across OpenAI and Anthropic.

Lambda Labs GPU Cloud

lambda-labs-gpu-cloud

Orchestra-Research/AI-Research-SKILLs

Lambda Labs GPU cloud offers reserved and on-demand instances with SSH access, persistent filesystems, and 1-Click multi-node clusters, making it ideal for long-running training and inference workloads that need high-performance GPUs.

LangChain Error Diagnostics

langchain-common-errors

jeremylongshore/claude-code-plugins-plus-skills

Guide to diagnose and fix LangChain authentication, import, rate limit, parsing, chain, agent, and memory failures, plus debugging tips and tracing resources for integrations.

LangChain Agent Workflow

langchain-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

Build LangChain agents that combine tools, decision-making, and async workflows for autonomous task execution, piping outputs through streaming or history-aware sessions and handling parsing or tool errors.

LangChain Upgrade Guide

langchain-upgrade-migration

jeremylongshore/claude-code-plugins-plus-skills

Guides teams through checking versions, updating imports, migrating chains/agents/memories, upgrading packages, and validating tests when moving between LangChain releases.

LLM Observability Tracing

sickn33/antigravity-awesome-skills

Instrument Langfuse into LLM workflows to capture traces, metrics, prompt versions, and A/B test results, so you can monitor cost, latency, and quality alongside prompt-driven fixes.

LangGraph Agent Architecture

sickn33/antigravity-awesome-skills

Guides architects in building production-grade AI agents with LangGraph, emphasizing explicit graph structures, reducer-based state management, persistence, and tool-supported workflows.

Memory System Design

sickn33/antigravity-awesome-skills

Design layered short-term, long-term, and graph-based memory systems so agents persist across sessions, keep entity consistency, and reason over accumulated knowledge during conversations.

MLflow Lifecycle Tracker

Orchestra-Research/AI-Research-SKILLs

MLflow provides a framework-agnostic ML lifecycle toolkit for tracking experiments, logging models/artifacts, managing registries with versions/stages, and deploying across platforms so teams can reproduce and collaborate on PyTorch, TensorFlow, and Scikit-Learn workflows.

LLM Model Pruning

Orchestra-Research/AI-Research-SKILLs

Model Pruning skill applies Wanda, SparseGPT, structured, unstructured, and N:M sparsity to trim LLMs by around 50% and boost inference on accelerators or edge devices without retraining.

Perplexity Pitfalls Guide

perplexity-known-pitfalls

jeremylongshore/claude-code-plugins-plus-skills

A concise reference for spotting and avoiding Perplexity Sonar anti-patterns during reviews, onboarding, or audits, covering citation parsing, model selection, recency handling, and context limits so integrations stay accurate and cost-effective.

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