📚 AI Knowledge Base

Understanding AI model evaluation metrics

• What is MMLU? Massive Multitask Language Understanding benchmark explained
• What is HumanEval? Code generation benchmark for evaluating programming ability
• What is HellaSwag? Commonsense reasoning benchmark explained
• What is ARC? AI2 Reasoning Challenge for grade-school science questions

Technical concepts behind AI models

• What is Context Length? Understanding token windows and memory in LLMs
• What are Model Parameters? Why 7B, 70B, and model size matters
• What is a Transformer? The architecture behind modern language models

Guide to major AI model families

• Llama Family Guide Meta's LLaMA series from 7B to 70B
• Qwen Family Guide Alibaba's Qwen series and capabilities
• Mistral Family Guide Mistral AI's efficient model lineup

Running and deploying AI models

• How to Run LLMs Locally Complete guide to running models on your machine
• What is GGUF? Quantized model formats for efficient inference
• What is Ollama? Easy local LLM deployment tool explained

Understanding Free2AITools metrics

• What is FNI? Fair Nexus Index - our model trust score explained
• What is Deploy Score? Model deployability measurement explained

Core concepts and architectures

• Transformer Architecture The architecture behind modern language models
• Mixture of Experts (MoE) Efficient scaling with conditional computation
• Model Quantization GGUF, GPTQ, AWQ formats explained
• VRAM Requirements Memory needs for running LLMs
• Local Inference Running models on your own hardware