#Tokenizer

The project investigates how AI models grasp Chinese through analyses of character recognition and word vector distribution. It examines character mappings and Unicode representations to reveal how these models, including BERT, ERNIE, and XLM-Roberta, compare in handling Chinese semantics versus languages like Japanese and Korean. The findings serve as a crucial reference for future evaluations.

Discover the effective Typescript and C# implementations of byte pair encoding tokenizer optimized for OpenAI LLMs, building on OpenAI's tiktoken for smooth prompt tokenization in both Node.js and .NET platforms. Critical for developers moving from Microsoft.DeepDev.TokenizerLib to the enhanced Microsoft.ML.Tokenizers, scheduled for release with .NET 9.0. Contributions are welcome, following Microsoft's trademark and branding guidelines.

Learn to construct your own language model using this detailed repository inspired by nanoGPT and Shakespeare generator. It provides comprehensive tools from data gathering to model training, suitable for crafting BERT and GPT models. This repository is ideal for those familiar with Python 3.8 or above, offering clear instructions on processing data and training models. Perfect for AI developers seeking to tailor language model solutions, it ensures an organized setup, encouraging customization and innovation in language generation.