GGML
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About
GGML is an innovative tensor library built for machine learning, specifically designed to facilitate the execution of large AI models with high performance on widely available, commodity hardware. It features a low-level, cross-platform implementation with broad hardware support, integer quantization, and operates with zero memory allocations during runtime, requiring no third-party dependencies. GGML is minimal in its approach, keeping the codebase simple. It embraces an 'Open Core' philosophy, making the library freely available under the MIT license and encouraging community contributions. The company ggml.ai supports the development, aiming to advance on-device inference capabilities.
Platform
Task
Features
• no third-party dependencies
• zero memory allocations during runtime
• broad hardware support
• integer quantization support
• low-level cross-platform implementation
• on-device inference support
• open core development
• minimal codebase
Pricing Plans
Open Source
Free Plan• Low-level cross-platform implementation
• Integer quantization support
• Broad hardware support
• No third-party dependencies
• Zero memory allocations during runtime
• MIT license
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