Plain C/C++ CLIP inference, dependency-free
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This project provides a dependency-free C/C++ implementation of OpenAI's CLIP model, enabling efficient inference on resource-constrained devices. It targets developers and researchers needing to integrate CLIP for tasks like semantic search or zero-shot labeling without the overhead of large ML frameworks. The key benefit is a lightweight, fast inference engine with minimal dependencies.
How It Works
Leveraging the GGML library, clip.cpp offers highly optimized inference with support for 4-bit, 5-bit, and 8-bit quantization. This approach significantly reduces model size and memory footprint, making it suitable for edge devices and serverless deployments. It supports text-only, vision-only, and two-tower CLIP variants, providing flexibility for various applications.
Quick Start & Requirements
pip install clip_cpp
(for X64 Linux with AVX2). For other systems or instruction sets, build from source with cmake -DBUILD_SHARED_LIBS=ON ..
and make
.clip-cpp-gguf
).Highlighted Details
Maintenance & Community
The project is actively maintained. Recent updates include Clojure bindings and a switch to the GGUF model format. Discussions and support can be found via GitHub issues.
Licensing & Compatibility
The project is licensed under the MIT License, permitting commercial use and integration with closed-source applications.
Limitations & Caveats
Image preprocessing uses linear interpolation, which may differ numerically from PIL's bicubic interpolation with antialiasing. The GGUF format is a breaking change from previous .bin
files.
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