Nimendra's Notes 🪴

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00.Fleeting Notes

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Hands-on Large Language Models

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1. An Introduction to LLM

1. An Introduction to LLM

Backlinks

1. Introduction to AI Agents
2. LLMs and AI Agents
1. Introduction to LLMs
2. Pre-Training Data
3. Vocabulary and Tokenization
LLM Post Training
1. An Introduction to LLM
2. Tokens and Embeddings
Attention is All You Need (Transformers)
Decoder-Only Transformers (GPT)
Encoder-Only Transformers (BERT)
Hands-on Large Language Models
7. RAG - Retrieval as Context Selection
KV cache
How Compaction Works in Pi Agent
DeepSeek's DSpark

Language AI
History of Language AI
Bag-of-Words
Word2Vec
Types of Embeddings
Encoding and Decoding Context with Attention
Autoregressive Generation
Context Embedding
Attention
Representation Models : Encoder-Only Models
Generative Models: Decoder-Only Models
How it Works ?
Training Data
Model Parameters
Representation Models vs Generative Models
Large Language Models (LLMs)
From Completion Models to Chat Models
Context Window (Context Length)
The Training Paradigm of LLM
1. Language Modeling (Pretraining)
2. Fine-Tuning (Post-Training)
Related

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