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Found 72 Skills
Build text-to-speech applications using Qwen3-TTS, a powerful speech generation system supporting voice clone, voice design, and custom voice synthesis. Use when creating TTS applications, generating speech from text, cloning voices from audio samples, designing new voices via natural language descriptions, or fine-tuning TTS models. Supports 10 languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian).
This skill provides comprehensive guidance for using the Replicate CLI to run AI models, create predictions, manage deployments, and fine-tune models. Use this skill when the user wants to interact with Replicate's AI model platform via command line, including running image generation models, language models, or any ML model hosted on Replicate. This skill should be used when users ask about running models on Replicate, creating predictions, managing deployments, fine-tuning models, or working with the Replicate API through the CLI.
Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques. it is triggered when the user requests assistance with fine-tuning a model, adapting a pre-trained model to a new dataset, or performing... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
Implement comprehensive image editing capabilities in Blazor applications using the Syncfusion Image Editor component. Use this skill when implementing image editing, annotations, transformations, cropping, filtering, zooming, and panning features. Supports annotations (text, shapes, freehand), transformations (crop, rotate, flip, resize), effects (filters, fine-tuning), toolbar customization, and keyboard shortcuts.
Fine-tune LLMs using the Tinker API. Covers supervised fine-tuning, reinforcement learning, LoRA training, vision-language models, and both high-level Cookbook patterns and low-level API usage.
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engineering AI/ML skills.
Use when launching cloud VMs, Kubernetes pods, or Slurm jobs for GPU/TPU/CPU workloads, training or fine-tuning models on cloud GPUs, deploying inference servers (vllm, TGI, etc.) with autoscaling, writing or debugging SkyPilot task YAML files, using spot/preemptible instances for cost savings, comparing GPU prices across clouds, managing compute across 25+ clouds, Kubernetes, Slurm, and on-prem clusters with failover between them, troubleshooting resource availability or SkyPilot errors, or optimizing cost and GPU availability.
Cosmos-Embed1 video-text embedding for text-to-video retrieval, video-to-video search, semantic deduplication, and fine-tuning. Use when the user asks to "fine-tune Cosmos-Embed1", "run cosmos-embed inference", "export Cosmos-Embed1", "embed videos", or "search videos with text".
Guidelines for creating high-quality datasets for LLM post-training (SFT/DPO/RLHF). Use when preparing data for fine-tuning, evaluating data quality, or designing data collection strategies.
Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training
Builds production AI/ML systems — model training, fine-tuning, MLOps pipelines, model serving, evaluation frameworks, RAG optimization, and agent orchestration at scale. Use when the user asks to build, train, or deploy ML models, set up MLOps pipelines, optimize RAG systems, create inference endpoints, or design production AI agents.