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replied to their post about 12 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 🤖 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

reacted to openfree's post with 🧠 1 day ago

📊 Papers Impact: Instant AI Grading for Your Research Papers! 🚀 🌟 Introduction Hello, AI research community! 🎉 Introducing Papers Impact - the revolutionary AI tool that automatically grades and predicts the potential impact of research papers! 🧠💡 https://huggingface.co/spaces/VIDraft/PapersImpact ✨ Key Feature: Instant Paper Grading The core functionality is brilliantly simple: Just enter an arXiv paper ID or URL, and our AI instantly analyzes and grades the paper's potential academic impact! No need to read through the entire paper yourself - our system automatically evaluates the title and abstract to generate a normalized impact score between 0 and 1. 🎯 How It Works Enter Paper ID or URL: Simply paste an arXiv ID (e.g., "2504.11651") or full URL Automatic Fetching: The system retrieves the paper's title and abstract AI Analysis: Our advanced LLaMA-based transformer model analyzes the content Instant Grading: Receive an impact score and corresponding letter grade in seconds! 💡 Who Can Benefit? 🔬 Researchers: Pre-assess your paper before submission 📚 Students: Quickly gauge the quality of papers for literature reviews 🏫 Educators: Objectively evaluate student research 📊 Research Managers: Prioritize which papers to read in depth 🧩 Journal Editors: Get an AI second opinion on submissions 🚀 Technical Details Our model is trained on an extensive dataset of published papers in CS.CV, CS.CL, and CS.AI fields, using NDCG optimization with Sigmoid activation and MSE loss. It's been rigorously cross-validated against historical citation data to ensure accurate impact predictions.

reacted to openfree's post with ➕ 1 day ago

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replied to their post about 12 hours ago

I'll let people judge

I invested considerable time to solve various issues and shared the results as open source with everyone. It's widely known that when duplicating a repository on Huggingface, there is complete transparency about which account duplicated from which, and what modifications were made.
I am fully aware of these open source principles and transparency standards, and have improved upon existing open source work (particularly focusing on resolving and enhancing multilingual support issues) before releasing it again as open source. Criticizing this effort for allegedly not explicitly citing the lineage seems to focus excessively on formalities rather than appreciating the essence of contribution and improvement.
I believe the core value of open source lies in continuous improvement and sharing. My work aimed to make a genuine contribution aligned with these values.

reacted to openfree's post with 🧠➕ 1 day ago

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3876

📊 Papers Impact: Instant AI Grading for Your Research Papers! 🚀

🌟 Introduction
Hello, AI research community! 🎉
Introducing Papers Impact - the revolutionary AI tool that automatically grades and predicts the potential impact of research papers! 🧠💡

VIDraft/PapersImpact

✨ Key Feature: Instant Paper Grading
The core functionality is brilliantly simple: Just enter an arXiv paper ID or URL, and our AI instantly analyzes and grades the paper's potential academic impact! No need to read through the entire paper yourself - our system automatically evaluates the title and abstract to generate a normalized impact score between 0 and 1.
🎯 How It Works

Enter Paper ID or URL: Simply paste an arXiv ID (e.g., "2504.11651") or full URL
Automatic Fetching: The system retrieves the paper's title and abstract
AI Analysis: Our advanced LLaMA-based transformer model analyzes the content
Instant Grading: Receive an impact score and corresponding letter grade in seconds!

💡 Who Can Benefit?

🔬 Researchers: Pre-assess your paper before submission
📚 Students: Quickly gauge the quality of papers for literature reviews
🏫 Educators: Objectively evaluate student research
📊 Research Managers: Prioritize which papers to read in depth
🧩 Journal Editors: Get an AI second opinion on submissions

🚀 Technical Details
Our model is trained on an extensive dataset of published papers in CS.CV, CS.CL, and CS.AI fields, using NDCG optimization with Sigmoid activation and MSE loss. It's been rigorously cross-validated against historical citation data to ensure accurate impact predictions.

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reacted to fantos's post with 🤯 1 day ago

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4006

🎨 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 ![alt text](badge URL) 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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reacted to openfree's post with 👍 1 day ago

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4461

🧠 ThinkFlow: The Revolutionary Platform That Gives LLMs the Power to Think 🚀

Hello AI community! We're excited to introduce you to ThinkFlow, an innovative service that transforms how language models solve problems. 🎉
VIDraft/ThinkFlow-llama

✨ What is ThinkFlow?
ThinkFlow is a groundbreaking platform that automatically applies step-by-step reasoning capabilities to existing LLM models without any modifications. It makes complex problem-solving transparent, allowing you to witness the model's thought process in real-time.

🔍 Key Features

Reasoning Without Model Modifications: Add step-by-step reasoning while utilizing existing LLMs as they are ⚙️
Visualized Thinking Process: See exactly how the model analyzes and solves problems 👁️
Before & After Comparison: Compare standard responses with reasoning-enhanced outputs in real-time 📊
Improved Accuracy: Deliver more accurate solutions for complex math and logic problems 📈
Educational Value: Teach students systematic approaches to problem-solving 👨‍🏫
User-Friendly Interface: Intuitive and easy-to-use UI for seamless experience 🖥️

💡 What Problems Can It Solve?
ThinkFlow is particularly effective for various domains including:

Complex mathematical problems 🧮
Logic puzzles 🧩
Questions requiring multi-step reasoning 🤔
Scientific analysis challenges 🔬
Complex decision-making processes 📝

👨‍💻 Technical Details
ThinkFlow is built on the meta-llama/Llama-3.1-8B-Instruct model and uses carefully designed prompt chains to guide the model through step-by-step thinking. Each reasoning step builds upon the results of previous steps, culminating in a comprehensive final answer.

💬 Join Our Community!
If you have questions or suggestions about ThinkFlow, join our Discord community: https://discord.gg/openfreeai
Let's build better AI reasoning experiences together! 💪

#AI #LLM #ReasoningAI #ThinkFlow #HuggingFace #OpenSource #AIEducation

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reacted to ginipick's post with ❤️👀 1 day ago

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3619

🤖 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

reacted to seawolf2357's post with ❤️ 1 day ago

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4817

📚 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

reacted to their post with 👍🧠➕😎 1 day ago

Post

3920

🌐 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

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replied to their post 1 day ago

reacted to fantos's post with 😔🤝👍🧠➕😎🤗 2 days ago

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