Large Language Models (Using Huggingface)

Course Description:

The Large Language Models (Using Huggingface) is a 3-day developer class on working with Large Language Models. Students will learn how to use Transformers in Natural Language Processing and leverage the capabilities available on Huggingface.

Students will learn how transformer models work and their limitations, as well as how to fine-tune a pre-trained model using the Trainer API or Keras. The course will cover sharing models and tokenizers on the Hugging Face Hub and how to create your own dataset and perform a semantic search with FAISS using the Datasets library.

This 3-day course will take your Natural Language Processing projects to the next level.

TRANSFORMER MODELS
Natural Language Processing
Transformers, what can they do?
How do Transformers work?
Encoder models
Decoder models
Sequence-to-sequence models
Bias and limitations

USING TRANSFORMERS
Behind the pipeline
Models
Tokenizers
Handling multiple sequences
Putting it all together

FINE-TUNING A PRE-TRAINED MODEL
Processing the data
Fine-tuning a model with the Trainer API or Keras
A full training
Fine-tuning, Check!

SHARING MODELS AND TOKENIZERS
The Hugging Face Hub
Using pre-trained models
Sharing pre-trained models
Building a model card
Part 1 completed!
End-of-chapter quiz

THE DATASETS LIBRARY
What if my dataset isn't on the Hub?
Time to slice and dice
Big data? Datasets to the rescue!
Creating your own dataset
Semantic search with FAISS
Datasets

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