Total noob’s intro to Hugging Face Transformers
Welcome to "A Total Noob’s Introduction to Hugging Face Transformers," a guide designed specifically for those looking to understand the bare basics of using open-source ML. Our goal is to demystify what Hugging Face Transformers is and how it works, not to turn you into a machine learning practitioner, but to enable better understanding of and collaboration with those who are. That being said, the best way to learn is by doing, so we'll walk through a simple worked example of running Microsoft’s Phi-2 LLM in a notebook on a Hugging Face space.
You might wonder, with the abundance of tutorials on Hugging Face already available, why create another? The answer lies in accessibility: most existing resources assume some technical background, including Python proficiency, which can prevent non-technical individuals from grasping ML fundamentals. As someone who came from the business side of AI, I recognize that the learning curve presents a barrier and wanted to offer a more approachable path for like-minded learners.
Therefore, this guide is tailored for a non-technical audience keen to better understand open-source machine learning without having to learn Python from scratch. We assume no prior knowledge and will explain concepts from the ground up to ensure clarity. If you're an engineer, you’ll find this guide a bit basic, but for beginners, it's an ideal starting point.
Let’s get stuck in… but first some context.https://github.com/huggingface/blog/blob/main/noob_intro_transformers.md
Welcome to "A Total Noob’s Introduction to Hugging Face Transformers," a guide designed specifically for those looking to understand the bare basics of using open-source ML. Our goal is to demystify what Hugging Face Transformers is and how it works, not to turn you into a machine learning practitioner, but to enable better understanding of and collaboration with those who are. That being said, the best way to learn is by doing, so we'll walk through a simple worked example of running Microsoft’s Phi-2 LLM in a notebook on a Hugging Face space.
You might wonder, with the abundance of tutorials on Hugging Face already available, why create another? The answer lies in accessibility: most existing resources assume some technical background, including Python proficiency, which can prevent non-technical individuals from grasping ML fundamentals. As someone who came from the business side of AI, I recognize that the learning curve presents a barrier and wanted to offer a more approachable path for like-minded learners.
Therefore, this guide is tailored for a non-technical audience keen to better understand open-source machine learning without having to learn Python from scratch. We assume no prior knowledge and will explain concepts from the ground up to ensure clarity. If you're an engineer, you’ll find this guide a bit basic, but for beginners, it's an ideal starting point.
Let’s get stuck in… but first some context.https://github.com/huggingface/blog/blob/main/noob_intro_transformers.md
GitHub
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