Hugging Face is an AI community building the future. They provide tools that enable users to build, train and deploy ML models based on open source code and technologies.
Why this server?
Integrates with Hugging Face for model hosting and distribution, with links to MiniMax AI models on the platform.
Why this server?
Connects to MiniMax's Hugging Face organization to access related models and resources
Why this server?
Automatically downloads the latest OpenGenes database and documentation from Hugging Face Hub, ensuring access to up-to-date aging and longevity research data without manual file management
Why this server?
Allows interaction with the Hugging Face Dataset Viewer API, providing tools for browsing, searching, filtering, and analyzing datasets hosted on the Hugging Face Hub, along with support for authentication for private datasets.
Why this server?
Provides access to research papers hosted on Hugging Face, allowing users to discover and discuss AI/ML research
Why this server?
Allows retrieval of daily featured papers, trending models, and popular datasets from Hugging Face Hub, providing insights into the latest developments in machine learning models.
Why this server?
Uses Hugging Face's sentence transformers API to generate embeddings for semantic search in the RAG system, specifically leveraging the sentence-transformers/all-MiniLM-L6-v2 model for document and memory vectorization
Why this server?
Integrates with Hugging Face models for document embeddings, supporting the semantic search functionality.
Why this server?
Integrates with Hugging Face's LocalPythonExecutor from the smolagents framework to provide secure Python code execution capabilities with basic isolation and security for running LLM-generated Python code.