course documentation
Exam Time!
0. Setup
1. Transformer models
IntroductionNatural Language Processing and Large Language ModelsTransformers, what can they do?How do Transformers work?How 🤗 Transformers solve tasksTransformer ArchitecturesQuick quizInference with LLMsBias and limitationsSummaryCertification exam
2. Using 🤗 Transformers
IntroductionBehind the pipelineModelsTokenizersHandling multiple sequencesPutting it all togetherBasic usage completed!Optimized Inference DeploymentEnd-of-chapter quiz
3. Fine-tuning a pretrained model
IntroductionProcessing the dataFine-tuning a model with the Trainer APIA full training loopUnderstanding Learning CurvesFine-tuning, Check!End-of-chapter quiz
4. Sharing models and tokenizers
The Hugging Face HubUsing pretrained modelsSharing pretrained modelsBuilding a model cardPart 1 completed!End-of-chapter quiz
5. The 🤗 Datasets library
IntroductionWhat if my dataset isn't on the Hub?Time to slice and diceBig data? 🤗 Datasets to the rescue!Creating your own datasetSemantic search with FAISS🤗 Datasets, check!End-of-chapter quiz
6. The 🤗 Tokenizers library
IntroductionTraining a new tokenizer from an old oneFast tokenizers' special powersFast tokenizers in the QA pipelineNormalization and pre-tokenizationByte-Pair Encoding tokenizationWordPiece tokenizationUnigram tokenizationBuilding a tokenizer, block by blockTokenizers, check!End-of-chapter quiz
7. Classical NLP tasks
IntroductionToken classificationFine-tuning a masked language modelTranslationSummarizationTraining a causal language model from scratchQuestion answeringMastering LLMsEnd-of-chapter quiz
8. How to ask for help
IntroductionWhat to do when you get an errorAsking for help on the forumsDebugging the training pipelineHow to write a good issuePart 2 completed!End-of-chapter quiz
9. Building and sharing demos
Introduction to GradioBuilding your first demoUnderstanding the Interface classSharing demos with othersIntegrations with the Hugging Face HubAdvanced Interface featuresIntroduction to BlocksGradio, check!End-of-chapter quiz
10. Curate high-quality datasets
Introduction to ArgillaSet up your Argilla instanceLoad your dataset to ArgillaAnnotate your datasetUse your annotated datasetArgilla, check!End-of-chapter quiz
11. Fine-tune Large Language Models
IntroductionChat TemplatesFine-Tuning with SFTTrainerLoRA (Low-Rank Adaptation)EvaluationConclusionExam Time!
12. Build Reasoning Models new
IntroductionReinforcement Learning on LLMsThe Aha Moment in the DeepSeek R1 PaperAdvanced Understanding of GRPO in DeepSeekMathImplementing GRPO in TRLPractical Exercise to Fine-tune a model with GRPOPractical Exercise with UnslothComing soon...
Course Events
Exam Time!
It’s time to put your knowledge to the test! We’ve prepared a short quiz for you to test your understanding of the concepts covered in this chapter.
To take the quiz, you will need to follow these steps:
- Sign in to your Hugging Face account.
- Answer the questions in the quiz.
- Submit your answers.
Multiple Choice Quiz
In this quiz, you will be asked to select the correct answer from a list of options. We’ll test you on the fundamentals of supervised finetuning.
Code Quiz
In this quiz, you will be asked to write code to complete a task. We’ll test you on the code you’ve studied in the course from libraries like datasets, transformers, peft, and TRL.