Hugging Face has become one of the most popular open-source libraries for Artificial Intelligence.
It is a treasure for every enthusiast of Natural Language Processing tasks.
When you access the Hugging Face’s Language Model Hub you are in a complete new world of possibilities.
I started to experiment on my Google Colab Notebook every new feature I could. But the number of failures were greater than the success! When you run your code, following tutorials and examples, and 8/10 times you get an error you just want to give up!
If you want to learn new tool or library, it is beneficial to know beforehand the potential issues that may arise: things that one wishes they had known before diving in.
In this article we will explore 12 things every beginner should know. These tips will help you avoid common frustration and improve your progress with Hugging Face LLMs. They are split into 4 main topics:
1. Training course 2. Transformers and Pipelines 3. What Model sohuld I pick? 4. LangChain and Text2Text-generation
1. Training course
The Hugging Face Free Course is a free course on NLP using the HuggingFace ecosystem. It focuses on teaching the ins and outs of NLP and how to accomplish state-of-the-art tasks in NLP.
When you register to their portal the first thing you are asked for is to joining the free training course. I immediately clicked on yes (it is free…).
The course is divided into three major modules, each divided into chapters or subsections.