🔓 Unlock Custom Quantization for Hugging Face Models Locally with Ollama 🧠:

Author(s): Anoop Maurya

Originally published on Towards AI.

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If you’re familiar with Hugging Face, you already know it’s a massive hub for open-source machine learning models. But what if you want to run these models locally with minimal setup? Ollama makes that super easy, especially for GGUF models, a lightweight format optimized for running large-scale models efficiently.

This article will walk you through how to use Ollama to run any Hugging Face GGUF model on your machine, simplifying the process with just a few commands.

Ollama is a tool designed for running local large language models (LLMs). It provides an easy-to-use interface to run models directly from Hugging Face. The tool supports GGUF models — a specialized format optimized for running AI models on smaller hardware configurations like CPUs and GPUs without requiring the heavy compute resources often needed for LLMs.

Hugging Face is the go-to platform for machine learning models, with thousands of models across different tasks, ranging from natural language processing (NLP) to computer vision. Developers worldwide host their models on Hugging Face, making it an invaluable resource for anyone looking to build AI applications.

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Published via Towards AI