Data Science & ML Agent Skills
Discover Agent Skills for data science & ml. Browse 53skills for Claude, ChatGPT & Codex.
Llama.cpp Inference
Deploys and optimizes LLM inference on CPU, Apple Silicon, and consumer hardware using GGUF quantization.
Flash Attention Optimization
Optimizes Transformer models using Flash Attention to achieve significant speedups and memory reductions during training and inference.
PEFT Fine-Tuning
Fine-tunes large language models using LoRA, QLoRA, and other parameter-efficient methods to drastically reduce memory and compute requirements.
Long Context Transformer Extension
Extends transformer context windows using RoPE, YaRN, and ALiBi techniques to process documents exceeding 128k tokens.
LLaMA Factory Fine-Tuning
Streamlines the fine-tuning process for over 100 large language models using the LLaMA-Factory framework and QLoRA techniques.
DSPy Declarative AI Programming
Builds complex AI systems using Stanford's declarative programming framework to optimize prompts and create modular RAG systems automatically.
Whisper Speech Recognition
Transcribes audio, translates speech to English, and automates multilingual audio processing using OpenAI's Whisper models.
LangChain Framework
Builds LLM-powered applications using agents, retrieval-augmented generation (RAG), and modular chains.
CLIP Vision-Language Model
Enables zero-shot image classification and semantic image search by connecting visual concepts with natural language.
OpenRLHF Training Framework
Deploys high-performance Reinforcement Learning from Human Feedback (RLHF) workflows using Ray and vLLM acceleration for large-scale model alignment.
vLLM High-Performance Inference Serving
Serves Large Language Models with maximum throughput and efficiency using vLLM's PagedAttention and continuous batching.
GGUF Quantization & Model Optimization
Optimizes AI models for efficient local inference using the GGUF format and llama.cpp quantization techniques.
Speculative Decoding LLM Accelerator
Accelerates LLM inference speeds by up to 3.6x using advanced decoding techniques like Medusa heads and lookahead decoding.
BLIP-2 Multimodal Vision
Integrates Salesforce's BLIP-2 framework to enable advanced image captioning, visual question answering, and multimodal reasoning within AI workflows.
LLaVA Multimodal Assistant
Enables advanced vision-language capabilities for image understanding, multi-turn visual conversations, and document analysis.
PyTorch FSDP Expert
Optimizes large-scale AI model training using PyTorch Fully Sharded Data Parallelism for efficient memory management and scaling.
LlamaIndex RAG Framework
Connects LLMs to private data sources through advanced document ingestion, vector indexing, and retrieval-augmented generation (RAG) pipelines.
Model Merging & Fusion
Merges multiple fine-tuned AI models using mergekit to combine specialized capabilities like math and coding without expensive retraining.
NeMo Curator - GPU Data Curation
Curates high-quality datasets for LLM training using GPU-accelerated deduplication, filtering, and PII redaction.
nnsight Model Interpretability
Interprets and manipulates neural network internals for any PyTorch model, including massive foundation models via remote execution.
AudioCraft AI Generation
Generates high-fidelity music and sound effects from text descriptions using Meta's AudioCraft framework.
Outlines Structured Generation
Guarantees valid, type-safe JSON and structured outputs from Large Language Models using grammar-based constraints.
Ray Train Distributed Computing
Orchestrates distributed machine learning training across clusters to scale PyTorch, TensorFlow, and Hugging Face models.
GRPO RL Fine-Tuning
Implements Group Relative Policy Optimization (GRPO) using the TRL library to enhance model reasoning and structured output capabilities.
TensorBoard ML Visualization
Visualizes machine learning training metrics and model performance to streamline experiment tracking and model debugging.
Pinecone Vector Database Integration
Manages high-performance vector search and storage for production RAG and AI applications using Pinecone's serverless infrastructure.
LLM Guidance & Constrained Generation
Enforces structured LLM outputs using regex and grammars to guarantee valid JSON, XML, and code generation.
Constitutional AI Safety Alignment
Implements Anthropic's Constitutional AI method to train harmless, helpful models through self-critique and automated AI feedback.
RWKV Model Architecture
Implements and optimizes RWKV architectures, a hybrid RNN-Transformer model offering linear-time inference and infinite context windows.
SAELens: Mechanistic Interpretability
Decomposes complex neural network activations into sparse, interpretable features to understand and steer model behavior.
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