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Arhan Ayan

arhnayan
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replied to aiqtech's post about 22 hours ago
🌐 AI Token Visualization Tool with Perfect Multilingual Support Hello! Today I'm introducing my Token Visualization Tool with comprehensive multilingual support. This web-based application allows you to see how various Large Language Models (LLMs) tokenize text. https://huggingface.co/spaces/aiqtech/LLM-Token-Visual ✨ Key Features πŸ€– Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more πŸ”„ Custom Model Support: Use any tokenizer available on HuggingFace πŸ“Š Detailed Token Statistics: Analyze total tokens, unique tokens, compression ratio, and more 🌈 Visual Token Representation: Each token assigned a unique color for visual distinction πŸ“‚ File Analysis Support: Upload and analyze large files 🌏 Powerful Multilingual Support The most significant advantage of this tool is its perfect support for all languages: πŸ“ Asian languages including Korean, Chinese, and Japanese fully supported πŸ”€ RTL (right-to-left) languages like Arabic and Hebrew supported 🈺 Special characters and emoji tokenization visualization 🧩 Compare tokenization differences between languages πŸ’¬ Mixed multilingual text processing analysis πŸš€ How It Works Select your desired tokenizer model (predefined or HuggingFace model ID) Input multilingual text or upload a file for analysis Click 'Analyze Text' to see the tokenized results Visually understand how the model breaks down various languages with color-coded tokens πŸ’‘ Benefits of Multilingual Processing Understanding multilingual text tokenization patterns helps you: Optimize prompts that mix multiple languages Compare token efficiency across languages (e.g., English vs. Korean vs. Chinese token usage) Predict token usage for internationalization (i18n) applications Optimize costs for multilingual AI services πŸ› οΈ Technology Stack Backend: Flask (Python) Frontend: HTML, CSS, JavaScript (jQuery) Tokenizers: πŸ€— Transformers library
updated a model 2 months ago
arhnayan/unit4-handsonv2
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