Browse skills

Optimizes vector indexes for enhanced semantic search speed and accuracy by adjusting parameters like quantization levels.

Verl Rl Training — provides AI agent assistance for software development workflows.

Huggingface Tokenizers — provides AI agent assistance for software development workflows.

Provides search guidance and assistance for software development workflows.

Whisper — provides AI agent assistance for software development workflows.

Provides LangChain guidance and assistance for software development workflows.

Efficiently searches Qdrant vector databases using davila7's tool for semantic similarity and fast retrieval.

Deep Research — provides AI agent assistance for software development workflows.

Pinecone enables efficient semantic search by indexing and querying vector embeddings, quickly finding similar content for applications like recommendation & knowledge retrieval.

Company Research — provides AI agent assistance for software development workflows.

Helps with web development, search as part of software development workflows workflows.

Qdrant enables seamless vector database integration for semantic search and retrieval, boosting AI applications with efficient similarity matching.

This skill simplifies running and managing LLMs like VLLM, enabling efficient experimentation and deployment for developers and researchers.

This skill uses Sentence Transformers to generate high-quality embeddings for text, enabling semantic search and similarity analysis.

Faiss enables fast similarity search across large datasets by building indexes for efficient nearest neighbor retrieval – crucial for applications like recommendation and image search.

Generates high-quality embeddings from text using Grepai and LMStudio for semantic search, similarity analysis, and AI applications.

Generates OpenAI embeddings from text data using grepai's infrastructure for efficient vector representation and similarity search.

This skill integrates Upstash with Vector DBs for efficient similarity search and retrieval of vector embeddings, boosting AI applications.

Provides LLMs guidance and assistance for software development workflows.

Automatically expands limited training data with synthetic examples generated from web searches, boosting model accuracy.

This skill leverages vector databases to efficiently store and search semantic similarity between data points, enabling powerful retrieval-based AI applications.

Helps with AI, search, optimization as part of agent workflows workflows.

Serves LLMs like VLLM efficiently for experimentation and deployment, streamlining development workflows and scaling AI applications.

Provides LLMs guidance and assistance for building AI and machine learning applications.