Coding & Development

The Open LMM Reasoning Leaderboard is a platform designed to assess and compare the reasoning capabilities of Large Multimodal Models (LMMs). Hosted on Hugging Face Spaces, it provides a comprehensive overview of different LMMs, allowing users to filter and sort models based on criteria such as model name, size, and type. Researchers and developers can customize evaluation dimensions to gain specific insights into model performance metrics. This tool is invaluable for identifying top-performing LMMs and understanding their strengths and weaknesses in various reasoning tasks, contributing to advancements in AI model development and benchmarking.

The Open LMM Subjective Leaderboard is a specialized platform designed for evaluating the subjective performance of Large Multimodal Models (LMMs). It leverages the VLMEvalKit to generate comprehensive benchmark results, offering a clear and comparative view of various AI models. Users can browse and filter leaderboard data, input specific model names, and select different model sizes and types to refine their search. This tool is crucial for researchers and developers who need to assess and compare LMMs based on subjective criteria, helping them identify top-performing models and understand their strengths and weaknesses in real-world applications. The platform aims to provide detailed evaluation results to foster advancements in the field of multimodal AI.

Open Model Evolution is a platform designed for AI model development and experimentation, hosted as a Hugging Face Space. It provides users with the ability to create and explore interactive dashboards, which can include charts, tables, and various form controls. This tool is particularly useful for tracking the evolution of AI models over time, offering a visual and interactive way to monitor progress and changes. Furthermore, it supports researchers and developers in testing model improvements and experimenting with diverse model architectures, facilitating a deeper understanding and optimization of AI systems. The platform aims to streamline the process of AI model development and analysis within an open-source environment.

Prompt Depth Anything is an AI tool hosted on Hugging Face designed for depth estimation. Users can upload zip files from the Stray Scanner App, and the tool processes the first frame to produce a depth map, point cloud, and a 3D model of the captured scene. This functionality is particularly useful for AI enthusiasts and researchers who need to experiment with depth analysis in images and create 3D representations from real-world scans. The tool aims to provide high-resolution outputs for detailed scene reconstruction and analysis.

Pixel Reasoner is a Hugging Face Space developed by TIGER-Lab, designed for advanced visual reasoning. Users can upload images and interact with the AI by asking questions or providing text prompts to get detailed descriptions and analyses. A key feature is its ability to use these text prompts to intelligently understand and zoom into specific areas of interest within the images, enabling a more focused and in-depth examination. This tool is particularly useful for researchers and developers working in computer vision and AI, providing a platform to explore and test visual reasoning capabilities.

Quantization Dedup is a specialized tool hosted on Hugging Face Spaces, designed to help users visualize and understand the distribution of duplicate content within code repositories. It provides insights into how much content is shared between different files, which is crucial for optimizing storage, improving transfer efficiency, and managing codebases more effectively. The tool specifically focuses on deduplication from 'quants' in models like 'bartowski/gemma-2-9b-it-GGUF', indicating its relevance for analyzing and optimizing quantized AI models. By offering a clear view of content redundancy, Quantization Dedup assists developers and researchers in identifying areas for optimization within their AI infrastructure.

Prithvi 100M Burn Scars Demo is a specialized AI application designed for the detection of burn scars using HLS geotiff images. Developed by ibm-nasa-geospatial, this tool enables users to upload their own images, provided they contain specific channels in reflectance units. The application then processes these images to identify and highlight burn scars, outputting a color composite image as a result. This demonstration tool is part of the IBM-NASA Prithvi Models Family, showcasing capabilities in geospatial data analysis and AI model application for environmental monitoring.

Pinocchio Ita Leaderboard is a Hugging Face Space designed to showcase a comprehensive leaderboard of language model evaluations. This application provides users with the ability to filter and analyze evaluation results based on diverse criteria, including model type and precision. While the current live website indicates a build error, the tool's purpose is to offer a transparent and organized view of AI model performance, particularly for those interested in Italian language models. It aims to facilitate comparison and benchmarking within the AI community.

Predictive World Model 2024 is an AI model hosted on Hugging Face, specifically designed for predictive modeling and world model research. This application provides a comprehensive platform for participants in AI competitions, allowing them to easily access competition details, manage their submissions, and monitor their performance on leaderboards. Users can fetch detailed information about the competition, the dataset used, and the specific rules governing participation. It serves as a central hub for AI experimentation and forecasting, facilitating engagement and progress within the research community. The tool is currently running and accessible via its Hugging Face Space.

Python + HTTP Server is a straightforward tool designed for developers to create basic web servers using Python. It enables rapid setup of a server environment, facilitating the serving of files or the execution of simple web applications. This tool is particularly beneficial for those who require a quick and efficient method to test their code locally or share files within a development context. Its simplicity makes it an accessible option for various prototyping and testing needs, leveraging the power and versatility of Python for backend operations.

Podcastfy.ai offers an open-source alternative to NotebookLM's podcast feature, allowing users to transform various content types into engaging podcast scripts. Users can upload or paste text, provide website or YouTube URLs, and even include PDFs or images as source material. The tool provides options to customize the voice, conversation style, and length of the podcast, giving creators flexibility in their output. Once settings are chosen, the application crafts a script, streamlining the content creation process for podcasters and content creators looking to repurpose existing material into audio format. Being open-source, it's a valuable resource for those interested in research, education, and collaborative projects.

Qwen3-VL-2B-Instruct is an AI model hosted on Hugging Face Spaces, designed for multimodal interaction. Users can input text messages and optionally attach one or more images, and the AI will process both inputs to generate natural-language responses. This tool is ideal for research, experimentation, and applications requiring combined visual and textual understanding. It can be used for generating descriptions of images, analyzing visual content in conjunction with textual queries, or providing analytical insights based on multimodal data. The model offers a flexible platform for exploring the capabilities of large vision-language models.

Qwen3-VL-4B-Instruct is an AI model hosted on Hugging Face Spaces, designed for interactive multimodal chat. It allows users to upload images and text, then engage in conversations to obtain detailed descriptions and analysis. This tool is ideal for researchers, developers, and enthusiasts looking to experiment with advanced AI models that can process and understand both visual and textual information. While the current live website indicates a runtime error, the intended functionality is to provide a platform for exploring the capabilities of the Qwen3-VL model in a conversational setting, making it suitable for various AI-driven applications and research endeavors.

imbalanced-semi-self is an open-source GitHub repository offering implementation code for the paper "Rethinking the Value of Labels for Improving Class-Imbalanced Learning" presented at NeurIPS 2020. This tool focuses on enhancing performance on imbalanced (long-tailed) datasets by utilizing both semi-supervised learning (with unlabeled data) and self-supervised pre-training. It demonstrates how these techniques can improve class separation and mitigate tail class leakage, even with varying imbalanceness in labeled and unlabeled data. The repository includes code for training models with extra unlabeled data, self-supervised pre-training using Rotation prediction or MoCo, and network training with SSP models, supporting datasets like CIFAR, SVHN, ImageNet-LT, and iNaturalist 2018. It provides detailed instructions for installation, data preparation, pseudo-label generation, and testing pre-trained checkpoints.

Repainting 3D Assets is a specialized tool designed for modifying the textures and appearances of existing 3D models. This application enables users to customize their 3D assets, providing flexibility in design and aesthetic adjustments. While the live website content indicates the tool is currently sleeping due to inactivity, its core function is to facilitate the 'repainting' process, which implies changing colors, materials, or surface properties of 3D objects. This capability is particularly valuable for professionals in fields such as game development, architectural visualization, and 3D art, where unique and customized visual elements are crucial for projects.

RPC is a Hugging Face Space designed for evaluating math problems with different AI reasoning models. This application allows users to select a dataset, a specific model, and other parameters to load and evaluate mathematical problems. The primary purpose is to demonstrate and experiment with AI models for a NeurIPS 2025 paper. Users can observe the performance and results of various reasoning approaches, making it a valuable tool for academic research and model development in the field of AI and mathematics. The platform provides a hands-on environment for researchers and students to interact with cutting-edge AI models.

ROAM1RealWorldAdversarialAttack is a Hugging Face Space developed by Artificio, designed to facilitate participation in competitions focused on real-world adversarial attacks. This application provides a centralized platform for users to access crucial competition details, explore dataset information, and track their performance on leaderboards. It also offers functionalities for managing submissions, ensuring a streamlined process for participants. Furthermore, users can review competition rules and update their team names directly within the application, making it a comprehensive tool for researchers and security professionals involved in assessing the robustness and vulnerabilities of AI systems through adversarial attack simulations.

Repo Graph is an interactive visualization tool hosted on Hugging Face Spaces, designed to help users understand the structure of software repositories. By providing a repository name or URL, the application generates a visual graph that maps out the repository’s files, folders, and their interconnections. This byte-level map allows for quick exploration and comprehension of a project's architecture, making it easier to analyze code dependencies, identify key components, and understand the overall organization of AI models or other software projects. It's particularly useful for those working with the Hugging Face Hub, offering a unique perspective on its vast collection of models and datasets.

Repository statistics is a tool designed to provide comprehensive insights into software repositories, particularly focusing on open-source projects. It enables users to analyze various aspects of repository activity, track contributions from developers, and monitor the overall health and progress of a project. By offering detailed statistics, the tool helps maintainers and contributors understand engagement patterns, identify key contributors, and assess the impact of their work. This functionality is crucial for evaluating the success and sustainability of open-source initiatives, making it a valuable asset for anyone involved in managing or contributing to such projects.

HIVE Digital Technologies Ltd is a global leader in sustainable data center infrastructure, pioneering digital transformation through AI solutions and Bitcoin mining. The company builds and operates next-generation Tier-I and Tier-III data centers powered by clean energy across Canada, Sweden, and Paraguay. HIVE's dual-engine infrastructure, driven by Tier-I computing services and GPU-based accelerated AI computing, delivers scalable, environmentally responsible solutions for the digital economy. With a fleet of thousands of next-generation GPUs, HIVE is well-positioned to support the fast-growing AI and HPC markets, significantly expanding its global footprint through strategic acquisitions and data center deployments.

Screenshot To Html is a web-based application hosted on Hugging Face Spaces that transforms screenshots into functional HTML and CSS code. Users provide a description or an image of a desired web page, and the tool generates the corresponding static HTML output. This capability is particularly beneficial for web developers and designers who need to rapidly prototype web pages or convert design mockups into code. The application streamlines the initial coding phase, allowing for quicker iteration and development of web interfaces. It focuses on generating the core structure and styling, making it a practical solution for creating simple web pages or foundational layouts.

S2S-Arena is a specialized AI evaluation tool designed for assessing Speech-to-Speech (S2S) models. Hosted as a Hugging Face Space by FreedomIntelligence, it offers a platform where users can listen to audio samples generated by various S2S models. The primary function is to compare how effectively these models follow instructions and maintain semantic integrity during speech transformation. This tool is invaluable for researchers, developers, and anyone involved in the development and testing of S2S technologies, providing a direct way to evaluate and benchmark model performance against specific criteria. It helps in understanding the strengths and weaknesses of different S2S approaches.

ShieldGemma2 VLM is a multimodal safety model designed to evaluate and test the safety of AI models by analyzing images. Users can upload an image and define specific safety policies using descriptive text. The tool then processes the image against these policies, returning a probability score for each policy, indicating the likelihood of the image complying or violating the defined safety guidelines. This functionality makes it a valuable resource for researchers and developers focused on AI safety, vulnerability assessment, and ensuring responsible AI deployment. It helps in identifying potential risks and non-compliance in visual content based on user-defined criteria.

SmolLM3 WebGPU is a cutting-edge dual reasoning AI model developed by Hugging Face Smol Models Research. This innovative tool distinguishes itself by running entirely locally within a web browser, leveraging WebGPU technology. It provides a platform for AI enthusiasts and developers to directly interact with and experiment with advanced AI models without the need for complex setups or cloud infrastructure. The model's local execution ensures privacy and potentially faster response times, making it an ideal environment for testing new ideas and understanding AI behavior. As an open-source offering, it fosters community collaboration and allows for transparent development and customization.