segment-anything-model

Streamlines AI research workflows by providing curated Claude skills for data analysis, literature review, experiment design, and research paper generation.

Assists AI researchers in drafting, structuring, and generating machine learning research papers with academic writing best practices and technical precision.

Streamlines distributed machine learning training using Ray, optimizing hyperparameter tuning and parallel model execution across compute clusters.

Streamlines distributed data processing and machine learning workflows using Ray's scalable data loading and transformation capabilities.

Quantize and compress large language models using GPTQ for efficient inference and reduced memory footprint on various hardware.

Streamlines large-scale distributed machine learning training for transformer models using PyTorch Titan, optimizing GPU utilization and model performance

Streamlines parameter-efficient fine-tuning of large language models using Transformers Reinforcement Learning (TRL) techniques and best practices.

Orchestrates collaborative AI agents using CrewAI to solve complex tasks through dynamic role assignment, task delegation, and intelligent workflow management.

Provides structured, context-aware advice and recommendations for complex problem-solving, research workflows, and strategic decision-making

Systematically assess machine learning code generation models by benchmarking performance, identifying strengths/weaknesses, and generating comparative metrics.