Transformer

The Transformer Models Training is an intensive two-day course focusing on the practical application of state-of-the-art NLP models, such as BERT and GPT, using Hugging Face and TensorFlow Hub.

Duration

16h · 2 days

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Who it's for

Ideal for teams that…

1 Developers and data engineers who want to expand their skills with the latest NLP techniques

2 IT specialists who want to use transformer models for language processing automation

3 Data scientists and analysts looking to process and analyze text with advanced models

Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

How to install and configure Hugging Face and TensorFlow Hub for working with transformer models

✓

How to apply transformer models to text classification, named entity recognition (NER), and text generation

✓

How to use and fine-tune pretrained transformer models such as BERT and GPT

✓

How to optimize model performance and deploy models into production environments

Requirements

What you should know before we start

Basic knowledge of Python programming
Experience with cloud services is an advantage
Basic knowledge of machine learning

Program · 8 modules

What we actually do

Day 1: Introduction to Transformer Models and Hugging Face Basics

M01

Fundamentals of transformer models

· Introduction to transformer architecture: history and evolution
· Key components and core principles

M02

Overview of Hugging Face and TensorFlow Hub

· Installation and configuration of libraries
· Survey of available models and their applications

M03

Basic operations with transformer models

· Tokenization and text preprocessing
· Loading and using pretrained models

M04

Implementing transformers in text processing tasks

· Hands-on exercises: loading and testing models
· Analyzing results and basic optimization

Day 2: Advanced Techniques and Practical Applications

M05

Training and fine-tuning transformer models

· Techniques for training and fine-tuning pretrained models
· Using custom datasets for training

M06

Applications of transformer models

· Text classification
· Named Entity Recognition (NER)
· Text generation and machine translation
· Sentiment analysis

M07

Fine-tuning and applications

· Implementing fine-tuning on real-world datasets
· Building projects with BERT and GPT

M08

Model optimization and deployment

· Techniques for optimizing model performance
· Deploying models in production environments

Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.

How we work

From brief to retro in 30 days.

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

✓Quote within 48h of the brief

✓First session within 30 days

✓Pilot before the full decision

✓VAT invoice, payment in instalments possible

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