Features
Build a GPT-like LLM from scratch in PyTorch
Implement tokenization and data preprocessing
Design multi-head self-attention and transformer blocks
Train on text corpora with efficient batching
Fine-tune the model for instruction following
Explore alignment techniques (RLHF basics)
Evaluate model performance and generation quality
Includes code for inference and decoding strategies
Covers practical aspects like GPU memory optimization
Step-by-step code with explanations and illustrations
Official LLM leaderboard and ranking
Battle Mode for side-by-side model comparison
Agent Mode for real-world agent evaluation
Multimodal Max for multimodal model testing
Code Arena with web development challenge categories
BullshitBench for nonsense detection evaluation
File upload for third-party AI processing
Public conversation sharing for community research
Leaderboard dataset publicly available
Monthly arena updates across product and research
Search functionality for models and conversations
Community voting on model responses
