Abstract: Quantization is a critical technique employed across various research fields for compressing deep neural networks (DNNs) to facilitate deployment within resource-limited environments. This ...

Abstract: Quantization is a widely adopted technique to reduce the storage cost of neural networks. However, existing methods primarily focus on minimizing the ...

Large language models (LLMs) are increasingly being deployed on edge devices—hardware that processes data locally near the data source, such as smartphones, laptops, and robots. Running LLMs on these ...

Have you ever wished you could generate interactive websites with HTML, CSS, and JavaScript while programming in nothing but Python? Here are three frameworks that do the trick. Python has long had a ...

One of the most widely used techniques to make AI models more efficient, quantization, has limits — and the industry could be fast approaching them. In the context of AI, quantization refers to ...

In artificial intelligence, one common challenge is ensuring that language models can process information quickly and efficiently. Imagine you’re trying to use a language model to generate text or ...

I'm using llama-cpp-python==0.2.60, installed using this command CMAKE_ARGS="-DLLAMA_METAL=on" pip install llama-cpp-python. I'm able to load a model using type_k=8 and type_v=8 (for q8_0 cache).

HuggingFace Researchers introduce Quanto to address the challenge of optimizing deep learning models for deployment on resource-constrained devices, such as mobile phones and embedded systems. Instead ...

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I am an AI Reseach Engineer. I was formerly a researcher @Oxford VGG before founding the AI Bites YouTube channel. I am an AI Reseach Engineer. I was formerly a researcher @Oxford VGG before founding ...