Showing 4 open source projects for "mac runtime"

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    Spice.ai OSS

    Spice.ai OSS

    A self-hostable CDN for databases

    Spice is a portable runtime offering developers a unified SQL interface to materialize, accelerate, and query data from any database, data warehouse, or data lake. Spice connects, fuses, and delivers data to applications, machine-learning models, and AI backends, functioning as an application-specific, tier-optimized Database CDN. The Spice runtime, written in Rust, is built-with industry-leading technologies such as Apache DataFusion, Apache Arrow, Apache Arrow Flight, SQLite, and DuckDB....
    Downloads: 28 This Week
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  • 2
    shimmy

    shimmy

    Python-free Rust inference server

    The shimmy project is a lightweight local inference server designed to run large language models with minimal overhead. Written primarily in Rust, the tool provides a small standalone binary that exposes an API compatible with the OpenAI interface, allowing existing applications to interact with local models without significant code changes. This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture...
    Downloads: 3 This Week
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  • 3
    rust-bert

    rust-bert

    Rust native ready-to-use NLP pipelines and transformer-based models

    rust-bert is a Rust-based implementation of transformer-based natural language processing models that provides ready-to-use pipelines for tasks such as text classification, summarization, and question answering. The project ports many capabilities of the Hugging Face Transformers ecosystem into the Rust programming language. It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory...
    Downloads: 0 This Week
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  • 4
    Weld

    Weld

    High-performance runtime for data analytics applications

    Weld is a programming language and runtime designed to improve the performance of data-intensive applications by optimizing computations across multiple libraries. Instead of optimizing individual functions independently, Weld introduces an intermediate representation that allows different frameworks to share optimization opportunities. This approach reduces data movement between libraries and enables the system to generate highly optimized machine code for parallel execution. Weld is...
    Downloads: 0 This Week
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