LLM Fine-Tuning with Hugging Face: LoRA, QLoRA, PEFT
Fine-tune BERT, T5, ViT, LLaMA-style models and Qwen3-TTS using Hugging Face Transformers, custom datasets, LoRA, QLoRA
Taught by â‹® KGP Talkie | Laxmi Kant
$9.99 with coupon (list $149.99 — save $140.00, 93% off)
Coupon Verified: August 27, 2026 · click Claim Coupon to apply the discount code
27AU···Course Overview — Key Takeaways
Verified details for this course — last checked August 27, 2026. Rating and student counts are Udemy's own published figures.
- Course Title
- LLM Fine-Tuning with Hugging Face: LoRA, QLoRA, PEFT
- Platform
- Udemy (coupon tracked by CoursesWyn)
- Instructor
- KGP Talkie | Laxmi Kant
- Coupon Last Checked
- August 27, 2026
- Level
- All levels
- Category
- Development
- Topic
- LLM Fine-Tuning
- Length
- 20 hours 30 minutes of on-demand video
- Language
- English
- Access
- Lifetime access on Udemy
- Certificate
- Certificate of completion
- Top Outcomes
- Understand Hugging Face Transformers and how Transformer models power modern NLP and Generative AI applications. · Use Hugging Face pipelines, checkpoints, datasets, tokenizers, Auto Classes, and Spaces for practical AI projects. · Learn Transformer architecture including attention, QKV vectors, encoder-decoder blocks, and positional encoding.
- Prerequisites
- Basic Python programming knowledge is required to follow the coding projects and fine-tuning notebooks. · Basic understanding of machine learning or deep learning will be helpful but not strictly required.
- Price
- $9.99 with coupon (list $149.99 — save $140.00, 93% off)
- Coupon
- Hit Claim Coupon — the discount applies at checkout
What You'll Learn
Practical skills and outcomes you'll gain from LLM Fine-Tuning with Hugging Face: LoRA, QLoRA, PEFT — taken from the official Udemy syllabus for Development learners.
Understand Hugging Face Transformers and how Transformer models power modern NLP and Generative AI applications.
Use Hugging Face pipelines, checkpoints, datasets, tokenizers, Auto Classes, and Spaces for practical AI projects.
Learn Transformer architecture including attention, QKV vectors, encoder-decoder blocks, and positional encoding.
Fine-tune transformers for text classification, question answering, natural language inference, text summarization, and machine translation.
Understand BERT architecture, masked language modeling, next sentence prediction, and BERT fine-tuning.
Fine-tune BERT for multi-class sentiment classification and build a Streamlit app for real-time prediction.
Fine-tune DistilBERT, MobileBERT, and TinyBERT for fake news detection and performance benchmarking.
Fine-tune Transformer models for NER, text summarization, image classification, and custom NLP tasks.
Requirements
What you need before enrolling in LLM Fine-Tuning with Hugging Face: LoRA, QLoRA, PEFT — prerequisites as listed by the instructor on Udemy.
Basic Python programming knowledge is required to follow the coding projects and fine-tuning notebooks.
Basic understanding of machine learning or deep learning will be helpful but not strictly required.
Basic NLP knowledge is useful, but important concepts are explained step by step in the course.
A computer with internet access is required. Google Colab or a GPU machine is recommended for training.
No prior Hugging Face experience is needed. You will learn Transformers and fine-tuning from the basics.
Overview
The full official description of LLM Fine-Tuning with Hugging Face: LoRA, QLoRA, PEFT — curriculum, teaching approach, and everything included with this Udemy coupon.
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Frequently Asked Questions
Common queries about this coupon, pricing, and enrollment. Answers reflect our last check on August 27, 2026.
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