# Lightweight

Gemma 3 is Google's latest open-source model, developed using research and technology from Gemini 2.0. It's a lightweight, high-performance model that runs on a single GPU or TPU, providing developers with powerful AI capabilities. Gemma 3 offers various sizes (1B, 4B, 12B, and 27B), supports over 140 languages, and boasts advanced text and visual reasoning capabilities. Its key advantages include high performance, low computational requirements, and extensive multilingual support, making it suitable for rapid AI application deployment on diverse devices. The launch of Gemma 3 aims to promote AI technology adoption and innovation, helping developers achieve efficient development across different hardware platforms.

SmolVLM2 is a lightweight video language model designed to generate related text descriptions or video highlights by analyzing video content. This model is efficient and has low resource consumption, making it suitable for running on various devices, including mobile devices and desktop clients. Its main advantages are the ability to quickly process video data and generate high-quality text output, providing strong technical support for video content creation, video analysis, and education. Developed by the Hugging Face team, it's positioned as an efficient, lightweight video processing tool and is currently in the experimental stage; users can try it for free.

AI Infra Guard is an AI infrastructure security assessment tool developed by Tencent. It focuses on discovering and detecting potential security risks in AI systems, supporting 28 AI framework fingerprint recognitions and covering more than 200 security vulnerability databases. The tool is lightweight, easy to use, requires no complex configuration, and features flexible matching syntax and cross-platform support. It provides an efficient assessment method for the security of AI infrastructure, helping enterprises and developers protect their AI systems from security threats.

rene.css is focused on creating simple, lightweight interface designs and is the first CSS framework prepared for AI-driven design-to-code workflows. It provides an ideal foundation for designers, developers, and AI tools, supporting utility classes and inline styles, customizable structures, and ready-to-use elements. Its primary advantages are simplicity, ease of use, and AI support, making it suitable for fast development and design processes.

Developed by Hugging Face, SmolVLM-256M is a multimodal model based on the Idefics3 architecture, designed for efficient image and text input processing. It can answer questions about images, describe visual content, or transcribe text, requiring less than 1GB of GPU memory for inference. The model excels in multimodal tasks while maintaining a lightweight architecture, making it suitable for deployment on edge devices. Its training data is sourced from The Cauldron and Docmatix datasets, covering a range of content including document understanding and image description, showcasing its broad application potential. Currently, this model is freely available on the Hugging Face platform, aiming to empower developers and researchers with robust multimodal processing capabilities.

SmolVLM-500M, developed by Hugging Face, is a lightweight multimodal model that belongs to the SmolVLM series. Based on the Idefics3 architecture, it focuses on efficient image and text processing tasks. The model can accept image and text inputs in any order and generate text outputs, making it suitable for tasks such as image description and visual question answering. Its lightweight design allows it to operate on resource-constrained devices while maintaining strong performance in multimodal tasks. The model is licensed under the Apache 2.0 license, enabling open-source and flexible usage scenarios.

Confucius-o1-14B is an inference model developed by the NetEase Youdao team, optimized based on Qwen2.5-14B-Instruct. It employs a two-stage learning strategy that automatically generates reasoning chains and summarizes step-by-step problem-solving processes. This model is aimed at the education field, particularly suitable for K12 math problems, helping users quickly acquire correct problem-solving strategies and answers. Its lightweight nature allows it to be deployed on a single GPU without quantization, reducing the barrier to use. Its reasoning capabilities have demonstrated outstanding performance in internal evaluations, providing robust technical support for AI applications in education.

kokoro-onnx is a text-to-speech (TTS) project based on the Kokoro model and ONNX runtime. It supports English and plans to support French, Japanese, Korean, and Chinese. The model offers near real-time performance on macOS M1 and provides a variety of voice options, including whispering. The model is lightweight, approximately 300MB (around 80MB when quantized). This project is open-source on GitHub under the MIT license, facilitating easy integration and use for developers.

Zasper is an integrated development environment (IDE) specially designed for data science, built from the ground up to support large-scale concurrent processing. It features minimal memory usage, exceptional speed, and the ability to handle numerous concurrent connections. Zasper is highly suitable for running REPL-style data applications like Jupyter Notebook. Its main advantages include efficient concurrent processing and lightweight resource consumption, making it of significant value in the data science field. Currently, Zasper is available as an open-source version, ideal for data scientists and developers.

YuLan-Mini is a lightweight language model developed by the AI Box team at Renmin University of China. With 240 million parameters, it achieves performance comparable to industry-leading models trained on larger datasets, despite using only 1.08 terabytes of pre-trained data. The model excels in mathematics and coding domains, and to facilitate reproducibility, the team will open-source relevant pre-training resources.

Bambo is a new type of proxy framework that stands out as more lightweight and flexible compared to mainstream frameworks, capable of managing a wide array of load tasks. The primary advantage of this framework lies in its flexibility and lightweight nature, which make it applicable in various scenarios, particularly when dealing with large volumes of data and requests. Bambo is designed to meet the demands for high efficiency and performance in modern software development. Currently, this framework is open source and available for free use.

Gemma 2 2B is a lightweight, advanced text generation model developed by Google, belonging to the Gemma model family. This model is built on the same research and technology as the Gemini model and is a text-to-text decoder consisting solely of a large language model, offering an English version. The Gemma 2 2B model is well-suited for various text generation tasks such as question answering, summarization, and reasoning, while its smaller model size enables deployment in resource-constrained environments like laptops or desktops, facilitating access to advanced AI models and fostering innovation.

Gemma is a series of lightweight, advanced open models developed by Google, built upon the same research and technology as the Gemini model. They are text-to-text decoder-only large language models suitable for a variety of text generation tasks, such as question answering, summarization, and reasoning. Gemma's relatively small size allows it to be deployed in resource-limited environments, such as laptops, desktops, or your own cloud infrastructure, making cutting-edge AI models accessible to everyone and fostering innovation.

Google Gemma is a cutting-edge lightweight open model developed by Google. It comes in 2B and 7B parameter versions, including base and fine-tuned versions. Built using Google's leading technology in base techniques and instruction tuning, Gemma adheres to AI principles to ensure safe and reliable use. Optimized for Google Cloud and NVIDIA GPUs, it offers global support.

Gemma is a series of open-source, lightweight language models launched by Google. It combines comprehensive safety measures with excellent performance in terms of size, even surpassing some larger open models. It is seamlessly compatible with various frameworks. It provides quick start guides, benchmarks, model access, and more, to help developers responsibly develop AI applications.

FreGrad is a lightweight and fast frequency-aware diffusion audio codec designed to generate realistic audio. Its framework includes discrete wavelet transform, frequency-aware expansion convolution, and a series of quality enhancement techniques for model generation. In experiments, FreGrad achieves a 3.7x speedup in training speed and a 2.2x speedup in inference speed compared to baseline models, while reducing model size by 0.6x (only 1.78 million parameters) without sacrificing output quality.

Felladrin MiniSearch is a lightweight search engine tool designed to help users quickly search through files and communities. Its fast and efficient search capabilities make it a powerful tool for boosting productivity. MiniSearch focuses on providing a simple and quick search experience, aiding users in quickly locating the information they need, whether in personal file management or community interactions.

SAM is a C++ image segmentation model built from scratch. It performs pixel-level segmentation on images, identifying object boundaries without requiring any additional code or annotations. Based on Meta's Segment Anything Model, SAM leverages a Transformer architecture for end-to-end image segmentation prediction. It offers a simple and easy-to-use C++ interface, supporting both command-line and graphical user interface modes. SAM efficiently runs on CPUs, boasting a compact model size while maintaining good segmentation accuracy. It's ideal for deploying and utilizing image segmentation models in resource-constrained embedded environments where high performance is required but GPUs are unavailable.

Firefly is an open-source, lightweight AI-powered note-taking center. It supports OCR image recognition collection, hotkey collection, text marking icon collection, and more. It has a powerful Markdown editor that supports almost all Markdown elements. Firefly also provides an AI assistant function that can process the collected information with AI and quickly collect the processed AI content. Firefly also offers Copilot Hub, an AI platform based on large model technology, where users can train models with their own data to build personal knowledge bases. It supports multiple usage scenarios, making work more efficient and intelligent.