A language model is a probabilistic model that learns to predict the probability of word sequences, enabling it to generate coherent and contextually appropriate text.
How they work:
• Learn from massive text datasets
• Predict the next word in a sequence
• Capture patterns and context
• Generate human-like text
🧠 Key Insight:
Language models don't truly "understand" text like humans do, but they become very good at statistical pattern matching and generation!
Types of Language Models
📊 N-gram Models
Statistical models based on word sequences (bigrams, trigrams)
🧠 Neural Language Models
RNN/LSTM-based models that capture longer dependencies
⚡ Transformer Models
Modern attention-based models like GPT and BERT
🚀 Large Language Models
Massive models with billions of parameters (GPT-3, GPT-4)
Interactive Text Generation Demo
Input Prompt
Generated Output
Click "Generate Text" to see AI-generated continuation...
GPT Series
Generative Pre-trained Transformers focused on text generation and completion.