caffe-cifar-10
Caffe CIFAR-10 Build and Training
This skill provides procedural guidance for building the Caffe deep learning framework from source and training models on the CIFAR-10 dataset.
When to Use This Skill
- Building Caffe from source on Ubuntu/Debian systems
- Training CIFAR-10 or similar image classification models with Caffe
- Configuring Caffe for CPU-only execution
- Troubleshooting Caffe build and dependency issues
Critical Requirements Checklist
Before starting, identify ALL requirements from the task specification:
- Execution mode: CPU-only vs GPU (affects solver configuration)
- Iteration count: Specific number of training iterations required
- Output files: Where training logs and models should be saved
- Model checkpoints: Which iteration's model file is expected
More from letta-ai/skills
extracting-pdf-text
Extract text from PDFs for LLM consumption. Use when processing PDFs for RAG, document analysis, or text extraction. Supports API services (Mistral OCR) and local tools (PyMuPDF, pdfplumber). Handles text-based PDFs, tables, and scanned documents with OCR.
257imessage
Send and read iMessages/SMS from macOS. Use for texting contacts, scheduling services, or automating message-based workflows. Triggers on queries about texting, messaging, SMS, iMessage, or contacting someone via text.
206video-processing
Guide for video analysis and frame-level event detection tasks using OpenCV and similar libraries. This skill should be used when detecting events in videos (jumps, movements, gestures), extracting frames, analyzing motion patterns, or implementing computer vision algorithms on video data. It provides verification strategies and helps avoid common pitfalls in video processing workflows.
189letta-api-client
Build applications with the Letta API — a model-agnostic, stateful API for building persistent agents with memory and long-term learning. Covers SDK patterns for Python and TypeScript. Includes 24 working code examples.
147google-workspace
Connect to Gmail and Google Calendar via OAuth 2.0. Use when users want to search/read emails, create drafts, search calendar events, check availability, or schedule meetings. Triggers on queries about email, inbox, calendar, schedule, or meetings.
127portfolio-optimization
Guidance for implementing high-performance portfolio optimization using Python C extensions. This skill applies when tasks require optimizing financial computations (matrix operations, covariance calculations, portfolio risk metrics) by implementing C extensions for Python. Use when performance speedup requirements exist (e.g., 1.2x or greater) and the task involves numerical computations on large datasets (thousands of assets).
101