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learned-skills-index
Index directory for automatically learned skills from execution feedback
☆ 13View skill
tools machine learning AI Skills
Discover tools machine learning skills, compare source repositories and read the instructions for each workflow.
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GitHub
agent-machine-learning-engineer
Expert ML engineer specializing in production model deployment, serving infrastructure, and scalable ML systems. Masters model optimization, real-time inference, and edge deployment with focus on reliability an...
☆ 13View skill
GitHub
agent-ml-engineer
Expert ML engineer specializing in machine learning model lifecycle, production deployment, and ML system optimization. Masters both traditional ML and deep learning with focus on building scalable, reliable ML...
☆ 13View skill
GitHub
agent-prompt-engineer
Expert prompt engineer specializing in designing, optimizing, and managing prompts for large language models. Masters prompt architecture, evaluation frameworks, and production prompt systems with focus on reli...
☆ 13View skill
GitHub
lora
Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specializ...
☆ 13View skill
GitHub
pytorch
Building and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pipelines, model optimization with torch.compile, distributed training, or deploying PyTorch...
☆ 13View skill
GitHub
transformers
Loading and using pretrained models with Hugging Face Transformers. Use when working with pretrained models from the Hub, running inference with Pipeline API, fine-tuning models with Trainer, or handling text,...
☆ 13View skill
GitHub
qlora
Memory-efficient fine-tuning with 4-bit quantization and LoRA adapters. Use when fine-tuning large models (7B+) on consumer GPUs, when VRAM is limited, or when standard LoRA still exceeds memory. Builds on the...
☆ 13View skill
GitHub
agents
Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven task...
☆ 13View skill
GitHub
mlx
Running and fine-tuning LLMs on Apple Silicon with MLX. Use when working with models locally on Mac, converting Hugging Face models to MLX format, fine-tuning with LoRA/QLoRA on Apple Silicon, or serving models...
☆ 13View skill
GitHub
digitalocean-agentic-cloud
DigitalOcean Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents on GPU infrastructure with foundation models, knowledge bases, and agent routes. Use when planning or opera...
☆ 12View skill
GitHub
mlops
MLOps engineering covering ML pipeline design, model versioning, experiment tracking, deployment strategies, drift detection, and monitoring for production ML systems with tools like MLflow, Kubeflow, and model...
☆ 12View skill
GitHub
model-development
Model-Development standards for model development in Ml Ai environments.
☆ 12View skill
GitHub
model-deployment
Model-Deployment standards for model deployment in Ml Ai environments.
☆ 12View skill
GitHub
google-adk-python
Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deplo...
☆ 11View skill
GitHub
verify-inference-example
Verify a CVlization inference example is properly structured, builds successfully, and runs inference correctly. Use when validating inference example implementations or debugging inference issues.
☆ 11View skill
GitHub
verify-training-pipeline
Verify a CVlization training pipeline example is properly structured, can build, trains successfully, and logs appropriate metrics. Use when validating example implementations or debugging training issues.
☆ 11View skill
GitHub
fiftyone-model-evaluation
Evaluate model predictions against ground truth using COCO, Open Images, or custom protocols. Use when computing mAP, precision, recall, confusion matrices, or analyzing TP/FP/FN examples for detection, classif...
☆ 11View skill
GitHub
fiftyone-dataset-export
Exports FiftyOne datasets to standard formats (COCO, YOLO, VOC, CVAT, CSV, etc.). Use when converting datasets, exporting for training, creating archives, or sharing data in specific formats.
☆ 11View skill
GitHub
fiftyone-dataset-import
Imports datasets into FiftyOne with automatic format detection. Supports all media types (images, videos, point clouds), label formats (COCO, YOLO, VOC, KITTI), and multimodal grouped datasets. Use when importi...
☆ 11View skill
GitHub
fiftyone-dataset-inference
Run ML model inference (YOLO, YOLOv8, CLIP, SAM, Detectron2, etc.) on FiftyOne datasets. Use when running models, applying detection, classification, segmentation, embeddings, or any model prediction task. Also...
☆ 11View skill
GitHub
pi-dcp
Dynamic Context Pruning extension for pi. Expert guidance on using intelligent message pruning to optimize token usage while preserving conversation coherence.
☆ 11View skill
GitHub
data-analysis
Perform data analysis tasks including data cleaning, statistical analysis, visualization, and insight generation. Use when the user asks to analyze data, perform statistical analysis, create visualizations, or...
☆ 11View skill
GitHub
agent-workflow
Expert system for designing and architecting AI agent workflows based on proven Meta methodologies. Use when users need to build AI agents, create agent workflows, solve problems using agentic systems, integrat...
☆ 10View skill
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.