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Awesome GitHub RepositoriesFramework-Specific Model Converters
Tools that transform trained models from specific frameworks like Fairseq, Hugging Face, and Marian into an optimized binary format.
Distinct from Model Quantization Frameworks: Distinct from Model Quantization Frameworks: focuses on converting models from specific training frameworks into a runtime format, not general quantization techniques.
Explore 1 awesome GitHub repository matching artificial intelligence & ml · Framework-Specific Model Converters. Refine with filters or upvote what's useful.
Awesome Framework-Specific Model Converters GitHub Repositories
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- opennmt/ctranslate2
OpenNMT/CTranslate2
4,319GitHub पर देखेंCTranslate2 is a C++ inference engine and runtime for Transformer models, designed to execute models on both CPU and GPU with optimizations for speed and memory efficiency. It functions as a model format converter, quantization tool, and REST API server, enabling deployment of neural machine translation, automatic speech recognition, and text generation models. The engine distinguishes itself through a suite of runtime optimizations including layer fusion, weight-matrix quantization, batch-by-length grouping, and a caching allocator that reuses GPU memory. It supports tensor-parallel model di
Converting trained models from frameworks like Fairseq and Hugging Face into an optimized binary format with weight quantization for efficient deployment.
C++avxavx2cpp
