← Back to courses
Artificial Intelligence and Machine Learning
NLP and Large Language Models with Hugging Face
Use, fine-tune and share Transformer models
A classroom course in working with language models. It follows the structure of the Hugging Face course: how Transformer models work, using models from the Hub, fine-tuning and sharing; the Datasets and Tokenizers libraries; classic NLP tasks; building a demo; and advanced topics including fine-tuning large language models and curating datasets. This course prepares for no exam.
11Modules
IntermediateLevel
3 monthsDuration
COURSE THUMBNAIL
What you will be able to do
Explain how Transformer models process language
Use a pretrained model for a language task
Prepare a dataset and tokenize it
Fine-tune a model and measure the result
Share a model and a working demo
Course outline
01
How Transformer models work
02
Using models from the Hugging Face Hub
03
Fine-tuning a pretrained model
04
Sharing models and results on the Hub
05
The Datasets library
06
The Tokenizers library
07
Classic NLP tasks: classification, question answering and summarisation
08
Building and sharing a demo
09
Fine-tuning large language models
10
Curating high-quality datasets
11
Project: a fine-tuned model with a working demo
Tools you will use
Hugging Face TransformersHugging Face DatasetsHugging Face TokenizersHugging Face HubPyTorchPython
What you need
Comfortable programming in Python
Deep learning basics (Deep Learning with PyTorch or equivalent)
