LLM : Transformer Architecture

1. 1Read the article on Medium to learn about the Transformer architecture
2. 2Identify the roles of the Encoder, Decoder, Attention, FFN, and Softmax in LLMs
3. 3Apply the knowledge to build or fine-tune an LLM model using a library like Hugging Face
4. 4Configure the model architecture to suit a specific NLP task
5. 5Test the model on a dataset to evaluate its performance

NLP engineers and data scientists can benefit from understanding the Transformer architecture to build and fine-tune LLMs

💡 The Transformer architecture is a key component of LLMs, enabling them to understand and generate human-like text

🤖 Learn the basics of Transformer architecture in LLMs! Encoder, Decoder, Attention, FFN, and Softmax work together to generate text