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Deepseek r1 0528 API
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Deepseek r1 0528 API with Real-time search
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4562
🌐 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
🤖 Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more
🔄 Custom Model Support: Use any tokenizer available on HuggingFace
📊 Detailed Token Statistics: Analyze total tokens, unique tokens, compression ratio, and more
🌈 Visual Token Representation: Each token assigned a unique color for visual distinction
📂 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:
📝 Asian languages including Korean, Chinese, and Japanese fully supported
🔤 RTL (right-to-left) languages like Arabic and Hebrew supported
🈺 Special characters and emoji tokenization visualization
🧩 Compare tokenization differences between languages
💬 Mixed multilingual text processing analysis
🚀 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
💡 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
🛠️ Technology Stack
Backend: Flask (Python)
Frontend: HTML, CSS, JavaScript (jQuery)
Tokenizers: 🤗 Transformers library
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
🤖 Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more
🔄 Custom Model Support: Use any tokenizer available on HuggingFace
📊 Detailed Token Statistics: Analyze total tokens, unique tokens, compression ratio, and more
🌈 Visual Token Representation: Each token assigned a unique color for visual distinction
📂 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:
📝 Asian languages including Korean, Chinese, and Japanese fully supported
🔤 RTL (right-to-left) languages like Arabic and Hebrew supported
🈺 Special characters and emoji tokenization visualization
🧩 Compare tokenization differences between languages
💬 Mixed multilingual text processing analysis
🚀 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
💡 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
🛠️ Technology Stack
Backend: Flask (Python)
Frontend: HTML, CSS, JavaScript (jQuery)
Tokenizers: 🤗 Transformers library
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🎨 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
🖌️ 14 diverse color options including vibrant neon colors
🔤 Custom text input for label and message
🖼️ Support for 2000+ logos via Simple Icons
🔗 Clickable link integration
👁️ Real-time preview
💻 Ready-to-use HTML code generation
📝 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
✅ 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")
💡 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  format
👨💻 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!
🔗 openfree/Badge
✨ Available under MIT License - feel free to use and modify.
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
🖌️ 14 diverse color options including vibrant neon colors
🔤 Custom text input for label and message
🖼️ Support for 2000+ logos via Simple Icons
🔗 Clickable link integration
👁️ Real-time preview
💻 Ready-to-use HTML code generation
📝 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
✅ 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")
💡 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  format
👨💻 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!
🔗 openfree/Badge
✨ Available under MIT License - feel free to use and modify.
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🤖 AI Academic Paper Generator: Your Research Partner 🎓
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
📚 Literature Research: AI reviews and summarizes relevant research
📝 Paper Outline: Generates a well-structured paper outline
✍️ Draft Writing: Creates a paper draft based on your research topic
🔗 Citation Generation: Automatically generates academic citations
🖋️ Editing & Polishing: Checks grammar, context, and logical flow
🌐 Multilingual Support: Interface available in English and Korean
🚀 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
💡 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! 💪
#AIResearch #AcademicWriting #ResearchAssistant #ArtificialIntelligence
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
📚 Literature Research: AI reviews and summarizes relevant research
📝 Paper Outline: Generates a well-structured paper outline
✍️ Draft Writing: Creates a paper draft based on your research topic
🔗 Citation Generation: Automatically generates academic citations
🖋️ Editing & Polishing: Checks grammar, context, and logical flow
🌐 Multilingual Support: Interface available in English and Korean
🚀 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
💡 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! 💪
#AIResearch #AcademicWriting #ResearchAssistant #ArtificialIntelligence
reacted to
aiqtech's
post with 🚀
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4562
🌐 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
🤖 Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more
🔄 Custom Model Support: Use any tokenizer available on HuggingFace
📊 Detailed Token Statistics: Analyze total tokens, unique tokens, compression ratio, and more
🌈 Visual Token Representation: Each token assigned a unique color for visual distinction
📂 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:
📝 Asian languages including Korean, Chinese, and Japanese fully supported
🔤 RTL (right-to-left) languages like Arabic and Hebrew supported
🈺 Special characters and emoji tokenization visualization
🧩 Compare tokenization differences between languages
💬 Mixed multilingual text processing analysis
🚀 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
💡 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
🛠️ Technology Stack
Backend: Flask (Python)
Frontend: HTML, CSS, JavaScript (jQuery)
Tokenizers: 🤗 Transformers library
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
🤖 Multiple LLM Tokenizers: Support for Llama 4, Mistral, Gemma, Deepseek, QWQ, BERT, and more
🔄 Custom Model Support: Use any tokenizer available on HuggingFace
📊 Detailed Token Statistics: Analyze total tokens, unique tokens, compression ratio, and more
🌈 Visual Token Representation: Each token assigned a unique color for visual distinction
📂 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:
📝 Asian languages including Korean, Chinese, and Japanese fully supported
🔤 RTL (right-to-left) languages like Arabic and Hebrew supported
🈺 Special characters and emoji tokenization visualization
🧩 Compare tokenization differences between languages
💬 Mixed multilingual text processing analysis
🚀 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
💡 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
🛠️ Technology Stack
Backend: Flask (Python)
Frontend: HTML, CSS, JavaScript (jQuery)
Tokenizers: 🤗 Transformers library
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📚 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
💡 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
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
💡 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
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