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claude-skills
claude-skills contains 10,000 collected skills from ssrjkk, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Checkpointing with Accelerate. model saving.
Data Loading with Accelerate. data pipelines.
Distributed with Accelerate. distributed training.
Inference with Accelerate. running models.
Optimization with Accelerate. model optimization.
Pruning with Accelerate. model pruning.
Quantization with Accelerate. model quantization.
Training with Accelerate. training models.
Transfer Learning with Accelerate. transfer learning.
Visualization with Accelerate. model viz.
Designs LLM agents with memory, tools, and reasoning cycle. Use for creating autonomous AI assistants.
Intro for Agentic: introduction
Usage for Agentic: usage reference
Automated code review with AI agents
Modern AI-assisted development workflow
AI safety and responsible AI practices
Color Processing with Albumentations. color manipulation.
Edge Detection with Albumentations. edge detection.
Face Detection with Albumentations. facial recognition.
Feature Extraction with Albumentations. extracting features.
Image Augmentation with Albumentations. data augmentation.
Image Classification with Albumentations. classifying images.
Image Filtering with Albumentations. image filters.
Object Detection with Albumentations. detecting objects.
Optical Flow with Albumentations. motion detection.
Segmentation with Albumentations. image segmentation.
Integrates Anthropic's Claude API for chat completions, messages, and tool use in applications.
Development with Aot: tools and best practices
Classification with Auto Sklearn. building classifiers.
Clustering with Auto Sklearn. grouping data.
Deployment with Auto Sklearn. model serving.
Experiment Tracking with Auto Sklearn. tracking experiments.
Feature Engineering with Auto Sklearn. creating features.
Hyperparameter Tuning with Auto Sklearn. optimizing params.
Model Selection with Auto Sklearn. choosing models.
Monitoring with Auto Sklearn. model monitoring.
Pipeline with Auto Sklearn. ML pipelines.
Regression with Auto Sklearn. predicting values.
Examples for Autogen: practical examples
Fundamentals for Autogen: core concepts