Скачать или смотреть T5 & BART Model Explained with Python Code | Google Colab Demo | LLM Series EP-5

In this video, I explain T5 and BART models with practical Python coding using Google Colab, as part of our LLM Series – Episode 5.
🔹 What is T5 (Text-to-Text Transfer Transformer)
🔹 What is BART (Bidirectional and Auto-Regressive Transformer)
🔹 Encoder–Decoder architecture in LLMs
🔹 Python implementation of T5 and BART
🔹 Running models using Hugging Face Transformers
🔹 Text generation & summarization demo
🔹 How these models are used in real-world NLP applications
📌 All the code shown in this video is executed live in Google Colab, making it easy for students and beginners to practice along.
This video is highly useful for: ✔ M.Tech / B.Tech students
✔ AI & NLP learners
✔ LLM beginners
✔ Anyone preparing for projects, research, or interviews
👉 Watch till the end to understand how theory connects with real Python code.
👍 Like | 🔔 Subscribe | 💬 Comment for doubts or code support
🧪 Tools & Technologies Used
Python
Google Colab
Hugging Face Transformers
T5 Model
BART Model
NLP & LLM Concepts
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BART model python
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LLM coding tutorial
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