Fine Tuning LLM with Hugging Face Transformers for NLP — 93% OFF Discount Coupon

Master Transformer models like Phi2, LLAMA; BERT variants, and distillation for advanced NLP applications on custom data

★4.4 out of 5
7,043 students
Created by KGP Talkie | Laxmi Kant
English
Updated May 2026

Quick Facts — Course Summary

Here's a quick overview of everything you need to know about Fine Tuning LLM with Hugging Face Transformers for NLP before you enroll:

•Course Name: Fine Tuning LLM with Hugging Face Transformers for NLP
•Platform: Udemy
•Instructor: KGP Talkie | Laxmi Kant
•Coupon Last Verified: May 12, 2026
•Level: Advanced
•Topic: Development
•Subtopic: LLM Fine-Tuning
•Total Time: 16h 30m of video content
•Language: English
•Access Type: Unlimited lifetime access + updates
•Certificate: Included upon completion from Udemy
•Main Skills: Understand transformers and their role in NLP. · Gain hands-on experience with Hugging Face Transformers. · Learn about relevant datasets and evaluation metrics.
•Requirements: Basic understanding of natural language processing (NLP) · Basic programming skills
•Current Price: $9.99 (was $149.99). You save $140.00 with 93% discount.
•How to Apply: Click the coupon button to activate your discount automatically
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Skills You'll Master

By the end of Fine Tuning LLM with Hugging Face Transformers for NLP, you'll have these practical skills:

✓Understand transformers and their role in NLP. .
✓Gain hands-on experience with Hugging Face Transformers. .
✓Learn about relevant datasets and evaluation metrics. .
✓Fine-tune transformers for text classification, question answering, natural language inference, text summarization, and machine translation. .
✓Understand the principles of transformer fine-tuning. .
✓Apply transformer fine-tuning to real-world NLP problems. .
✓Learn about different types of transformers, such as BERT, GPT-2, and T5. .
✓Hands-on experience with the Hugging Face Transformers library.

What You Need Before Starting

Before enrolling in Fine Tuning LLM with Hugging Face Transformers for NLP, make sure you have:

•Basic understanding of natural language processing (NLP)
•Basic programming skills
•Familiarity with machine learning concepts
•Access to a computer with a GPU

About This Udemy Course

The following is the full official course description for Fine Tuning LLM with Hugging Face Transformers for NLP as published on Udemy by instructor KGP Talkie | Laxmi Kant:

Do not take this course if you are an ML beginner. This course is designed for those who are interested in pure coding and want to fine-tune LLMs instead of focusing on prompt engineering. Otherwise, you may find it difficult to understand.

Welcome to "Mastering Transformer Models and LLM Fine Tuning", a comprehensive and practical course designed for all levels, from beginners to advanced practitioners in Natural Language Processing (NLP). This course delves deep into the world of Transformer models, fine-tuning techniques, and knowledge distillation, with a special focus on popular BERT variants like Phi2, LLAMA, T5, BERT, DistilBERT, MobileBERT, and TinyBERT.

Course Overview:

Section 1: Introduction
  • Get an overview of the course and understand the learning outcomes.
  • Introduction to the resources and code files you will need throughout the course.
Section 2: Understanding Transformers with Hugging Face
  • Learn the fundamentals of Hugging Face Transformers.
  • Explore Hugging Face pipelines, checkpoints, models, and datasets.
  • Gain insights into Hugging Face Spaces and Auto-Classes for seamless model management.
Section 3: Core Concepts of Transformers and LLMs
  • Delve into the architectures and key concepts behind Transformers.
  • Understand the applications of Transformers in various NLP tasks.
  • Introduction to transfer learning with Transformers.
Section 4: BERT Architecture Deep Dive
  • Detailed exploration of BERT's architecture and its importance in context understanding.
  • Learn about Masked Language Modeling (MLM) and Next Sentence Prediction (NSP) in BERT.
  • Understand BERT fine-tuning and evaluation techniques.
Section 5: Practical Fine-Tuning with BERT
  • Hands-on sessions to fine-tune BERT for sentiment classification on Twitter data.
  • Step-by-step guide on data loading, tokenization, and model training.
  • Practical application of fine-tuning techniques to build a BERT classifier.
Section 6: Knowledge Distillation Techniques for BERT
  • Introduction to knowledge distillation and its significance in model optimization.
  • Detailed study of DistilBERT, including loss functions and paper walkthroughs.
  • Explore MobileBERT and TinyBERT, with a focus on their unique distillation techniques and practical implementations.
Section 7: Applying Distilled BERT Models for Real-World Tasks like Fake News Detection
  • Use DistilBERT, MobileBERT, and TinyBERT for fake news detection.
  • Practical examples and hands-on exercises to build and evaluate models.
  • Benchmarking performance of distilled models against BERT-Base.
Section 8: Named Entity Recognition (NER) with DistilBERT
  • Techniques for fine-tuning DistilBERT for NER in restaurant search applications.
  • Detailed guide on data preparation, tokenization, and model training.
  • Hands-on sessions to build, evaluate, and deploy NER models.
Section 9: Custom Summarization with T5 Transformer
  • Practical guide to fine-tuning the T5 model for summarization tasks.
  • Detailed walkthrough of dataset analysis, tokenization, and model fine-tuning.
  • Implement summarization predictions on custom data.
Section 10: Vision Transformer for Image Classification
  • Introduction to Vision Transformers (ViT) and their applications.
  • Step-by-step guide to using ViT for classifying Indian foods.
  • Practical exercises on image preprocessing, model training, and evaluation.
Section 11: Fine-Tuning Large Language Models on Custom Datasets
  • Theoretical insights and practical steps for fine-tuning large language models (LLMs).
  • Explore various fine-tuning techniques, including PEFT, LORA, and QLORA.
  • Hands-on coding sessions to implement custom dataset fine-tuning for LLMs.
Section 12: Specialized Topics in Transformer Fine-Tuning
  • Learn about advanced topics such as 8-bit quantization and adapter-based fine-tuning.
  • Review and implement state-of-the-art techniques for optimizing Transformer models.
  • Practical sessions to generate product descriptions using fine-tuned models.
Section 13: Building Chat and Instruction Models with LLAMA
  • Learn about advanced topics such as 4-bit quantization and adapter-based fine-tuning.
  • Techniques for fine-tuning the LLAMA base model for chat and instruction-based tasks.
  • Practical examples and hands-on guidance to build, train, and deploy chat models.
  • Explore the significance of chat format datasets and model configuration for PEFT fine-tuning.
Enroll now in "Mastering Transformer Models and LLM Fine Tuning on Custom Dataset" and gain the skills to harness the power of state-of-the-art NLP models. Whether you're just starting or looking to enhance your expertise, this course offers valuable knowledge and practical experience to elevate your proficiency in the field of natural language processing.

Unlock the full potential of Transformer models with our comprehensive course. Master fine-tuning techniques for BERT variants, explore knowledge distillation with DistilBERT, MobileBERT, and TinyBERT, and apply advanced models like RoBERTa, ALBERT, XLNet, and Vision Transformers for real-world NLP applications. Dive into practical examples using Hugging Face tools, T5 for summarization, and learn to build custom chat models with LLAMA.

Keywords: Transformer models, fine-tuning BERT, DistilBERT, MobileBERT, TinyBERT, RoBERTa, ALBERT, XLNet, ELECTRA, ConvBERT, DeBERTa, Vision Transformer, T5, BART, Pegasus, GPT-3, DeiT, Swin Transformer, Hugging Face, NLP applications, knowledge distillation, custom chat models, LLAMA.

Is the Fine Tuning LLM with Hugging Face Transformers for NLP Coupon Worth It?

Expert review by Andrew Derek, Lead Course Analyst at CoursesWyn.•Last updated: May 12, 2026.

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Fine Tuning LLM with Hugging Face Transformers for NLP is a high-value resource for learners seeking to build skills inDevelopment. Taught by KGP Talkie | Laxmi Kant on Udemy, the 16h 30m course provides a structured progression from foundational concepts to advanced techniques— making it suitable for learners at all levels. The current coupon reduces the price by 93%, from $149.99 to $9.99, removing the primary financial barrier to enrollment.

✓What We Like (Pros)

  • Verified 93% price reduction makes this course accessible to learners on any budget.
  • Aggregate student rating of 4.4 out of 5 indicates high learner satisfaction.
  • Strong enrollment base with over 7,043 students demonstrates course popularity and trust.
  • Includes an official Udemy completion certificate and lifetime access to all future content updates.

!Keep in Mind (Cons)

The following limitations should be considered before enrolling in Fine Tuning LLM with Hugging Face Transformers for NLP:

  • The depth of Development coverage may be challenging for absolute beginners without the listed prerequisites.
  • Lifetime access is contingent on the continued operation of the Udemy platform.
  • Hands-on projects and quizzes require additional time investment beyond video watch time.
Final Verdict: Worth It
This course offers exceptional value with current pricing
✓

Course Rating Summary

Fine Tuning LLM with Hugging Face Transformers for NLP Course holds an aggregate rating of 4.4 out of 5 based on 7,043 student reviews on Udemy.

4.4
★★★★★
7,043 Verified Ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy.

Instructor Profile

The following section provides background information on KGP Talkie | Laxmi Kant, the instructor responsible for creating and maintaining Fine Tuning LLM with Hugging Face Transformers for NLP on Udemy.

Fine Tuning LLM with Hugging Face Transformers for NLP is taught by KGP Talkie | Laxmi Kant, a Udemy instructor specializing in Development. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.

•Instructor Name: KGP Talkie | Laxmi Kant
•Subject Area: Development
•Teaching Approach: Practical, project-based instruction focused on real-world application of Development skills.

Frequently Asked Questions

The following questions and answers cover the most common queries about Fine Tuning LLM with Hugging Face Transformers for NLP, its coupon code, pricing, and enrollment process.

About the Author

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Andrew Derek

Lead Course Analyst at CoursesWyn with 8+ years of experience evaluating online learning platforms. I've analyzed 500+ Udemy courses and helped thousands of learners choose the right courses for their career goals.

⭐4.8/5 Rating
✓Trusted by 10K+ Students

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