Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Enables advanced vision-language capabilities for image understanding, multi-turn visual conversations, and document analysis.
Serves Large Language Models with maximum throughput and efficiency using vLLM's PagedAttention and continuous batching.
Builds complex AI systems using Stanford's declarative programming framework to optimize prompts and create modular RAG systems automatically.
Enables zero-shot image classification and semantic image search by connecting visual concepts with natural language.
Optimizes AI models for efficient local inference using the GGUF format and llama.cpp quantization techniques.
Accelerates LLM inference speeds by up to 3.6x using advanced decoding techniques like Medusa heads and lookahead decoding.
Merges multiple fine-tuned AI models using mergekit to combine specialized capabilities like math and coding without expensive retraining.
Optimizes large-scale AI model training using PyTorch Fully Sharded Data Parallelism for efficient memory management and scaling.
Interprets and manipulates neural network internals for any PyTorch model, including massive foundation models via remote execution.
Accelerates LLM fine-tuning workflows with Unsloth to achieve up to 5x faster training speeds and 80% reduced memory consumption.
Manages high-performance vector search and storage for production RAG and AI applications using Pinecone's serverless infrastructure.
Implements Group Relative Policy Optimization (GRPO) using the TRL library to enhance model reasoning and structured output capabilities.
Visualizes machine learning training metrics and model performance to streamline experiment tracking and model debugging.
Enforces structured LLM outputs using regex and grammars to guarantee valid JSON, XML, and code generation.
Implements and optimizes RWKV architectures, a hybrid RNN-Transformer model offering linear-time inference and infinite context windows.
Manages the machine learning lifecycle by tracking experiments, versioning models, and streamlining production deployments.
Evaluates Large Language Models across 60+ academic benchmarks to measure reasoning, coding, and mathematical capabilities using industry-standard metrics.
Streamlines deep learning development by decoupling research code from engineering boilerplate for automated distributed training and hardware scaling.
Accelerates large-scale similarity search and clustering for dense vectors using Facebook AI's high-performance library.
Generates high-quality images and performs advanced image transformations using Stable Diffusion models and the HuggingFace Diffusers library.
Detects system hardware capabilities and provides optimized computational strategies for scientific and data-intensive tasks.
Empowers Claude to create, analyze, and format professional Excel spreadsheets and financial models with automated formula recalculation.
Automates electronic lab notebook workflows by providing programmatic access to LabArchives for research data management and documentation.
Generates publication-quality scientific diagrams, neural network architectures, and flowcharts using specialized Python libraries.
Accesses the Reactome database to perform biological pathway analysis, gene mapping, and enrichment studies for systems biology.
Facilitates programmatic access to the ClinicalTrials.gov API v2 for advanced trial discovery, patient matching, and medical research data extraction.
Builds and deploys production-grade bioinformatics pipelines as serverless workflows on the Latch platform.
Facilitates creative scientific problem-solving by generating hypotheses and exploring interdisciplinary connections as a research ideation partner.
Searches and retrieves life sciences preprints from the bioRxiv database by keywords, authors, and categories.
Accesses and analyzes over 240 million scholarly works, authors, and institutions via the OpenAlex API for automated scientific discovery.
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