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AAAbstract Algorithmsabstractalgorithms.devMar 14 · 17 min read

Types of LLM Quantization: By Timing, Scope, and Mapping

TLDR: There is no single "best" LLM quantization. You classify and choose quantization along three axes: when you quantize (timing), what you quantize (scope), and how values are encoded (mapping). In

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AAAbstract Algorithmsabstractalgorithms.devMar 8 · 13 min read

LLM Model Quantization: Why, When, and How to Deploy Smaller, Faster Models

TLDR: Quantization converts high-precision model weights and activations (FP16/FP32) into lower-precision formats (INT8 or INT4) so LLMs run with less memory, lower latency, and lower cost. The key is

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SSeci84seci84.hashnode.devJul 23, 2025 · 3 min read

About Me

I’m an AI engineer with extensive experience in model development, optimization, and deployment. My passion lies in building intuitive and efficient ecosystems and platforms for developers. I believe that the future of AI lies in the seamless integra...

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OKOmkar Kastureomkarkasture.hashnode.devFeb 5, 2025 · 3 min read

Deep Learning with Keras and TesorFlow

Custom Training Loop Custom Training Loops: These provide more control over the training process compared to the standard Keras fit method. You can tailor the training to specific needs, such as implementing complex strategies or custom loss function...

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DKDeepak Kumar Mohantykumarblog-1.hashnode.devOct 26, 2024 · 5 min read

Residuals vs. Cost Functions: Key Differences in Machine Learning Evaluation

When it comes to evaluating machine learning models, two key concepts stand out: residuals and cost functions. These terms play a crucial role in determining how well our model predicts outcomes. In this blog post, we will explore these concepts in d...

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JCJuan Carlos Olamendyjuancolamendy.hashnode.devJul 29, 2024 · 6 min read