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reacted to aiqtech's post with ā¤ļø about 3 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 šŸ¤– Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more šŸ”„ Custom Model Support: Use any tokenizer available on HuggingFace šŸ“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 šŸ“‚ File Analysis Support: Upload and analyze large files šŸŒ Powerful Multilingual Support The most significant advantage of this tool is its perfect support for all languages: šŸ“ Asian languages including Korean, Chinese, and Japanese fully supported šŸ”¤ RTL (right-to-left) languages like Arabic and Hebrew supported 🈺 Special characters and emoji tokenization visualization 🧩 Compare tokenization differences between languages šŸ’¬ Mixed multilingual text processing analysis šŸš€ 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 šŸ’” 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 šŸ› ļø Technology Stack Backend: Flask (Python) Frontend: HTML, CSS, JavaScript (jQuery) Tokenizers: šŸ¤— Transformers library
reacted to aiqtech's post with šŸ”„ about 3 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 šŸ¤– Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more šŸ”„ Custom Model Support: Use any tokenizer available on HuggingFace šŸ“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 šŸ“‚ File Analysis Support: Upload and analyze large files šŸŒ Powerful Multilingual Support The most significant advantage of this tool is its perfect support for all languages: šŸ“ Asian languages including Korean, Chinese, and Japanese fully supported šŸ”¤ RTL (right-to-left) languages like Arabic and Hebrew supported 🈺 Special characters and emoji tokenization visualization 🧩 Compare tokenization differences between languages šŸ’¬ Mixed multilingual text processing analysis šŸš€ 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 šŸ’” 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 šŸ› ļø Technology Stack Backend: Flask (Python) Frontend: HTML, CSS, JavaScript (jQuery) Tokenizers: šŸ¤— Transformers library
reacted to aiqtech's post with šŸ‘€ 1 day 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 šŸ¤– Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more šŸ”„ Custom Model Support: Use any tokenizer available on HuggingFace šŸ“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 šŸ“‚ File Analysis Support: Upload and analyze large files šŸŒ Powerful Multilingual Support The most significant advantage of this tool is its perfect support for all languages: šŸ“ Asian languages including Korean, Chinese, and Japanese fully supported šŸ”¤ RTL (right-to-left) languages like Arabic and Hebrew supported 🈺 Special characters and emoji tokenization visualization 🧩 Compare tokenization differences between languages šŸ’¬ Mixed multilingual text processing analysis šŸš€ 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 šŸ’” 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 šŸ› ļø Technology Stack Backend: Flask (Python) Frontend: HTML, CSS, JavaScript (jQuery) Tokenizers: šŸ¤— Transformers library
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reacted to aiqtech's post with ā¤ļøšŸ”„ about 3 hours ago
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3669
🌐 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.

aiqtech/LLM-Token-Visual

✨ Key Features

šŸ¤– Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more
šŸ”„ Custom Model Support: Use any tokenizer available on HuggingFace
šŸ“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
šŸ“‚ File Analysis Support: Upload and analyze large files

šŸŒ Powerful Multilingual Support
The most significant advantage of this tool is its perfect support for all languages:

šŸ“ Asian languages including Korean, Chinese, and Japanese fully supported
šŸ”¤ RTL (right-to-left) languages like Arabic and Hebrew supported
🈺 Special characters and emoji tokenization visualization
🧩 Compare tokenization differences between languages
šŸ’¬ Mixed multilingual text processing analysis

šŸš€ 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

šŸ’” 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

šŸ› ļø Technology Stack

Backend: Flask (Python)
Frontend: HTML, CSS, JavaScript (jQuery)
Tokenizers: šŸ¤— Transformers library
Ā·
reacted to aiqtech's post with šŸ‘€ 1 day ago
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3669
🌐 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.

aiqtech/LLM-Token-Visual

✨ Key Features

šŸ¤– Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more
šŸ”„ Custom Model Support: Use any tokenizer available on HuggingFace
šŸ“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
šŸ“‚ File Analysis Support: Upload and analyze large files

šŸŒ Powerful Multilingual Support
The most significant advantage of this tool is its perfect support for all languages:

šŸ“ Asian languages including Korean, Chinese, and Japanese fully supported
šŸ”¤ RTL (right-to-left) languages like Arabic and Hebrew supported
🈺 Special characters and emoji tokenization visualization
🧩 Compare tokenization differences between languages
šŸ’¬ Mixed multilingual text processing analysis

šŸš€ 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

šŸ’” 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

šŸ› ļø Technology Stack

Backend: Flask (Python)
Frontend: HTML, CSS, JavaScript (jQuery)
Tokenizers: šŸ¤— Transformers library
Ā·
reacted to fantos's post with šŸ”„ 2 days ago
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3475
šŸŽØ BadgeCraft: Create Beautiful Badges with Ease! ✨
Hello there! Today I'm introducing BadgeCraft, a simple app that lets you create stunning badges for your websites, GitHub READMEs, and documentation.

🌟 Key Features

šŸ–Œļø 14 diverse color options including vibrant neon colors
šŸ”¤ Custom text input for label and message
šŸ–¼ļø Support for 2000+ logos via Simple Icons
šŸ”— Clickable link integration
šŸ‘ļø Real-time preview
šŸ’» Ready-to-use HTML code generation

šŸ“ How to Use

Label - Enter the text to display on the left side of the badge (e.g., "Discord", "Version", "Status")
Message - Enter the text to display on the right side of the badge
Logo - Type the name of a logo provided by Simple Icons (e.g., "discord", "github")
Style - Choose the shape of your badge (flat, plastic, for-the-badge, etc.)
Color Settings - Select background color, label background color, and logo color
Link - Enter the URL that the badge will link to when clicked

āœ… Use Cases

Add social media links to your GitHub project README
Display version information or download links on your website
Include tech stack badges in blog posts
Show status indicators in documentation (e.g., "in development", "stable")

šŸ’” Tips

Click on any of the prepared examples to automatically fill in all settings
Copy the generated HTML code and paste directly into your website or blog
HTML works in GitHub READMEs, but if you prefer markdown, use the ![alt text](badge URL) format

šŸ‘Øā€šŸ’» Tech Stack
This app was built using Gradio and leverages the shields.io API to generate badges. Its simple UI makes it accessible for everyone!

šŸ”— openfree/Badge

✨ Available under MIT License - feel free to use and modify.
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reacted to ginipick's post with šŸ‘€šŸš€šŸ”„ 3 days ago
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3565
šŸ¤– AI Academic Paper Generator: Your Research Partner šŸŽ“

Hello, researchers! Today I'm introducing my AI Academic Paper Generation System. This application is built with Streamlit and provides AI agents to assist with every stage of the academic research process.

ginipick/AgentX-Papers

✨ Key Features

šŸ“š Literature Research: AI reviews and summarizes relevant research
šŸ“ Paper Outline: Generates a well-structured paper outline
āœļø Draft Writing: Creates a paper draft based on your research topic
šŸ”— Citation Generation: Automatically generates academic citations
šŸ–‹ļø Editing & Polishing: Checks grammar, context, and logical flow
🌐 Multilingual Support: Interface available in English and Korean

šŸš€ How to Use

Enter basic information like research topic, paper title, and deadline
AI agents generate everything from literature review to final paper
Download your completed paper or consult with the chatbot for further assistance

šŸ’” What Makes It Special
This tool integrates all stages of academic research. Going beyond simple text generation, it mimics the actual research process to produce higher quality papers.
Visualization features and social media sharing options will be added in the next update! šŸ’Ŗ

#AIResearch #AcademicWriting #ResearchAssistant #ArtificialIntelligence
reacted to aiqtech's post with šŸš€ 3 days ago
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3669
🌐 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.

aiqtech/LLM-Token-Visual

✨ Key Features

šŸ¤– Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more
šŸ”„ Custom Model Support: Use any tokenizer available on HuggingFace
šŸ“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
šŸ“‚ File Analysis Support: Upload and analyze large files

šŸŒ Powerful Multilingual Support
The most significant advantage of this tool is its perfect support for all languages:

šŸ“ Asian languages including Korean, Chinese, and Japanese fully supported
šŸ”¤ RTL (right-to-left) languages like Arabic and Hebrew supported
🈺 Special characters and emoji tokenization visualization
🧩 Compare tokenization differences between languages
šŸ’¬ Mixed multilingual text processing analysis

šŸš€ 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

šŸ’” 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

šŸ› ļø Technology Stack

Backend: Flask (Python)
Frontend: HTML, CSS, JavaScript (jQuery)
Tokenizers: šŸ¤— Transformers library
Ā·
reacted to seawolf2357's post with šŸ‘€ 3 days ago
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4681
šŸ“š Papers Leaderboard - See the Latest AI Research Trends at a Glance! ✨

Hello, AI research community! Today I'm introducing a new tool for exploring research papers. Papers Leaderboard is an open-source dashboard that makes it easy to find and filter the latest AI research papers.

Heartsync/Papers-Leaderboard

🌟 Key Features

Date Filtering: View only papers published within a specific timeframe (from May 5, 2023 to present)
Title Search: Quickly find papers containing your keywords of interest
Abstract Search: Explore paper content more deeply by searching for keywords within abstracts
Automatic Updates: The database is updated with the latest papers every hour

šŸ’” How to Use It?

Select a start date and end date
Enter keywords you want to find in titles or abstracts
Adjust the maximum number of search results for abstract searches
Results are displayed neatly in table format