Compare different tokenizers in char-level and byte-level.
Convert files to Markdown format
Provide feedback on text content
List the capabilities of various AI models
Classify Turkish text into predefined categories
Generate vector representations from text
Experiment with and compare different tokenizers
Easily visualize tokens for any diffusion model.
Test your attribute inference skills with comments
Generate topics from text data with BERTopic
Retrieve news articles based on a query
Search for similar AI-generated patent abstracts
Track, rank and evaluate open Arabic LLMs and chatbots
Tokenizer Arena is a tool designed for comparing different tokenizers at the char-level and byte-level. It allows users to explore and analyze how various tokenization methods process text, making it an essential resource for anyone working with text analysis and natural language processing (NLP). Tokenizer Arena provides a unified interface to examine tokenization outcomes, enabling insights into the strengths and weaknesses of different tokenizers.
What is a tokenizer, and why is it important?
A tokenizer is a tool that splits text into smaller units (tokens) based on predefined rules. It is crucial for NLP tasks like language modeling and text classification.
What input formats does Tokenizer Arena support?
Tokenizer Arena typically supports raw text, with options for importing files in formats like CSV or JSON.
What is the difference between char-level and byte-level tokenization?
Char-level tokenization splits text based on character boundaries, while byte-level tokenization splits text based on byte boundaries. Byte-level tokenization is often used in byte-based language models.