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openfree 
posted an update 1 day ago
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2004
🧠 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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seawolf2357 
posted an update about 9 hours ago
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671
📚 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
aiqtech 
posted an update about 10 hours ago
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566
🌐 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
ginipick 
posted an update about 10 hours ago
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418
🤖 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
m-ric 
posted an update 2 days ago
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1834
New king of open VLMs: InternVL3 takes Qwen 2.5's crown! 👑

InternVL have been a wildly successful series of model : and the latest iteration has just taken back their crown thanks to their superior, natively multimodal vision training pipeline.

➡️ Most of the vision language models (VLMs) these days are built like Frankenstein : take a good text-only Large Language Model (LLM) backbone, stitch a specific vision transformer (ViT) on top of it. Then the training is sequential 🔢 : 1. Freeze the LLM weights while you train the ViT only to work with the LLM part, then 2. Unfreeze all weights to train all weights in order to work together.

💫 The Shanghai Lab decided to challenge this paradigm and chose this approach that they call "native". For each of their model sizes, they still start from a good LLM (mostly Qwen-2.5 series, did I tell you I'm a huge fan of Qwen? ❤️), and stitch the ViT, but they don't freeze anything : they train all weights together with interleaved text and image understanding data in a single pre-training phase 🎨.

They claim it results in more seamless interactions between modalities. And the results prove them right: they took the crown of top VLMs, at nearly all sizes, from their Qwen-2.5 parents. 👑
  • 2 replies
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prithivMLmods 
posted an update 3 days ago
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2353
Dropping an entire collection of Style Intermixing Adapters on StrangerZone HF — including Realism, Anime, Sketch, Texture-Rich 3D Experimentals, Automotive Concept Images, and LoRA models based on Flux.1, SD 3.5 Turbo/Large, Stable Diffusion XL 🎨

╰┈➤Collection :
➜ sketch : strangerzonehf/sketch-fav-675ba869c7ceaec7e652ee1c
➜ sketch2 : strangerzonehf/q-series-sketch-678e3503bf3a661758429717
➜ automotive : strangerzonehf/automotive-3d-675bb31a491d8c264d45d843
➜ texture 3d : strangerzonehf/flux-3dxl-engine-674833c14a001d5b1fdb5139
➜ super 3d : strangerzonehf/super-3d-engine-6743231d69f496df97addd2b
➜ style mix : strangerzonehf/mixer-engine-673582c9c5939d8aa5bf9533
➜ realism : strangerzonehf/realism-engine-67343495b6daf0fbdb904cc1

╰┈➤The Entire Collection :
➜ flux.1 : prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
➜ flux-ultimate-lora-collection : strangerzonehf/Flux-Ultimate-LoRA-Collection
➜ sd 3.5 large / turbo : prithivMLmods/sd-35-large-lora-671b39d7bc2e7f71a446b163
➜ sdxl : prithivMLmods/sdxl-dev-models-667803a6d5ac75b59110e527

╰┈➤Pages :
➜ page 1: strangerzonehf
➜ page 2: @prithivMLmods
➜ demo : prithivMLmods/FLUX-LoRA-DLC

.🤗
nyuuzyou 
posted an update 1 day ago
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🦅 SmolLM2-Eagle Collection - nyuuzyou/smollm2-eagle-680263bf97f0c7e6bbe4936b

Collection of fine-tuned bilingual language models featuring:
- Models in three parameter sizes: 135M, 360M, and 1.7B based on HuggingFaceTB's SmolLM2 models
- Both standard and GGUF formats for flexible deployment in llama.cpp and Ollama
- Fine-tuned on nyuuzyou/EagleSFT dataset (536,231 Russian-English QA pairs derived from 739k+ real user queries)
- Experimental Russian language capabilities while maintaining English performance
- Limited Russian capabilities due to SFT-only approach without Russian pre-training
- Environmental impact: ~19.75 kg CO2eq

This collection provides compact models for research on bilingual language capabilities, resource-constrained environments, and educational applications. Not recommended for production use due to experimental nature and inherent limitations. Available under Apache 2.0 license.
  • 1 reply
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merterbak 
posted an update 1 day ago
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1386
Here’s a cool paper I found: “Massive Image Embedding Benchmark (MIEB).” It is a new tool to test how good image embedding models are. It has 130 different tasks grouped into 8 categories, like image search, classification, clustering similar images, answering questions based on images, and understanding documents. It even covers 38 different languages.

The authors tested 50 models and found that no single model was best at everything. Some models were great at recognizing text inside images but struggled to handle complicated tasks like matching images and text that appear together.

Paper: https://arxiv.org/pdf/2504.10471v1
Code: https://github.com/embeddings-benchmark/mteb
  • 2 replies
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educrpg 
posted an update 2 days ago
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1415
anyone have all their spaces stuck in building now?
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samuellimabraz 
posted an update 2 days ago
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I recently had the opportunity to present at a Computer Vision Hangout, sharing my journey from autonomous drone competition to fine-tuning Vision-Language Models.

I built an interactive presentation app! Here's a glimpse of the topics:

🚁 Black Bee Drones:
My first steps into CV with Latin America's first autonomous drone team. Covering classical CV techniques (filtering, edge detection), the IMAV 2023 mission (ArUco detection, line following with PID control), and links to demos for OpenCV basics and PID simulation.

🤖 Asimo Foundation:
Using MediaPipe for gesture control of a robotic arm in an educational project.

☕ CafeDL:
Building a small Deep Learning framework from scratch in Java (inspired by Keras, using ND4J) and training a CNN for a QuickDraw-like app.

🏢 Tech4Humans:
Real-world applications, including open-source signature detection and efficient fine-tuning of VLMs for document extraction.

Check out the interactive demos (also embedded in the main app):

1️⃣ CV Hangout App: The main presentation app showcasing my journey.
samuellimabraz/cv-hangout

2️⃣ OpenCV GUI: Real-time demo of CV techniques (filters, color filtering, ArUco) & AI models.
samuellimabraz/opencv-gui

3️⃣ Line Follow PID: Simulation of a PID controller for drone line-following.
samuellimabraz/line-follow-pid

I hope these resources are helpful to someone on their CV learning journey!
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