Model Storage Optimisation

AutoAWQ is an open-source tool designed to simplify the quantization of AI models to 4-bit precision, reducing storage a...

AutoGPTQ is a Python library that simplifies the quantization of large language models (LLMs) using the GPTQ algorithm, ...

AWQ (Activation-aware Weight Quantization) is a technique for compressing and accelerating large language models (LLMs) ...

GGML is a tensor library designed for machine learning, with a focus on optimizing storage and enabling efficient infere...

neural-compressor is an open-source tool developed by Intel that applies model compression techniques like quantization,...

NNEF (Neural Network Exchange Format) is a standardized format for storing and exchanging neural network models across d...

ONNX (Open Neural Network Exchange) is an open standard for representing machine learning models, enabling seamless conv...

PFA (Portable Format for Analytics) is a JSON-based standard designed for representing and exchanging predictive models ...

PMML (Predictive Model Markup Language) is an XML-based standard for representing predictive models, enabling interopera...

Quanto is a tool designed to optimize the storage and deployment of deep learning models through quantization, reducing ...