Lilly Tech Systems
Hugging Face NLP Certification
A complete exam prep course for the Hugging Face NLP Certification. This certification validates your ability to use the Transformers library for production NLP tasks — from pipelines and tokenizers to fine-tuning with Trainer API and LoRA, sharing models on the Hub, and building Gradio demos. Includes a 25-question practice assessment with detailed explanations.
Your Learning Path
Follow these lessons in order for complete Hugging Face NLP Certification preparation, or jump to any topic.
1. Certification Overview
HF certification program structure, assessment format, what is tested, registration process, and recommended study plan.
2. Transformers Library
Pipeline API, tokenizers, models, AutoClasses (AutoModel, AutoTokenizer), and practical usage patterns with practice questions.
3. Fine-Tuning
Trainer API, LoRA/PEFT, custom datasets, evaluation metrics, hyperparameter search, and practice questions.
4. NLP Tasks
Text classification, NER, question answering, summarization, and translation using Hugging Face with practice questions.
5. Model Sharing
Hugging Face Hub, model cards, Spaces, Gradio demos, pushing models, and community collaboration with practice questions.
6. Practice Assessment
25 exam-style questions covering all certification topics with detailed explanations and references.
7. Tips & FAQ
Exam day tips, study strategies, common mistakes, and a comprehensive FAQ accordion for last-minute review.
What You'll Learn
By the end of this course, you will be able to:
Use Transformers Library
Master the Pipeline API, tokenizers, AutoClasses, and model inference for any NLP task using Hugging Face Transformers.
Fine-Tune Models
Fine-tune pre-trained models with Trainer API and LoRA/PEFT on custom datasets with proper evaluation metrics.
Solve NLP Tasks
Build solutions for classification, NER, QA, summarization, and translation using the right model for each task.
Share on the Hub
Push models to the Hub, write model cards, deploy Gradio demos on Spaces, and collaborate with the community.