# open-source

Kimi-Dev is a powerful open-source coding LLM designed to tackle issues in software engineering. It is optimized through large-scale reinforcement learning to ensure correctness and robustness in real development environments. Kimi-Dev-72B achieved 60.4% performance on the SWE-bench benchmark, surpassing other open-source models, making it one of the most advanced coding LLMs available today. The model can be downloaded and deployed from Hugging Face and GitHub, making it suitable for use by developers and researchers.

Seed-Coder is a series of open-source code large language models launched by the Seed Team of ByteDance. It includes base, instruction, and reasoning models, aiming to significantly enhance programming capabilities through minimal human effort and autonomous management of code training data. The model performs excellently among similar open-source models and is suitable for various coding tasks. It is positioned to promote the development of the open-source LLM ecosystem and is applicable to both research and industry.

Ubicloud is an open-source cloud platform that can run anywhere. It provides elastic computing, block storage, load balancers, firewalls, managed PostgreSQL, and GitHub Actions runners. By using self-hosted software or managed services, you can reduce cloud costs by 3 to 10 times.

Zarin is an open-source AI platform that brings together over 200 popular and latest AI multi-models, providing users with functions such as generating images, videos, audio, code, and academic papers. Its main advantage is breaking the barrier of switching between different AI platforms, allowing users to complete multiple tasks on one platform. The background information of Zarin was developed by Ibrohim Abdivokhidov.

InternVL 2.5 is an advanced multimodal large language model series based on InternVL 2.0. While maintaining the core model architecture, it introduces significant enhancements in training and testing strategies as well as data quality. This model explores the relationship between model scalability and performance, systematically investigating performance trends across visual encoders, language models, dataset sizes, and test settings. Comprehensive evaluations across a wide range of benchmarks, including interdisciplinary reasoning, document understanding, multi-image/video comprehension, real-world understanding, multimodal hallucination detection, visual localization, multilingual capabilities, and pure language processing, demonstrate InternVL 2.5's competitiveness comparable to leading commercial models like GPT-4o and Claude-3.5-Sonnet. Notably, it is the first open-source MLLM to achieve over 70% on the MMMU benchmark, attaining a 3.7 percentage point improvement through Chain of Thought (CoT) reasoning, showcasing strong potential for scalability during testing.

Meme Search is an application that allows users to search memes through visual content and text indexation. It enables users to quickly find the memes they need by text search. The application uses natural language processing technology to automatically generate a text description from the image and store it as a vector index, which enables fast retrieval. The open-source nature and innovative search approach of Meme Search make it a powerful tool to improve meme search efficiency.

Gemma 2, the next-generation open-source AI model from Google DeepMind, offers 9 billion and 27 billion parameter versions with outstanding performance and inference efficiency. It supports full-precision, efficient operation on diverse hardware, significantly reducing deployment costs. Notably, the 27 billion parameter version of Gemma 2 delivers the performance of a model twice its size and can be run on a single NVIDIA H100 Tensor Core GPU or TPU host, significantly lowering deployment costs.

Milvus is an open-source vector database built specifically for similarity search on large, high-dimensional vectors. It supports pip installation, integrates seamlessly with popular AI development tools, and scales to billions of vectors. Milvus's efficient vector similarity search capabilities empower developers to build powerful and scalable image retrieval systems, whether managing personal photo libraries or developing commercial image search applications. It provides a robust foundation for unlocking the hidden value within image collections.

HyperCrawl is the first web crawler designed for LLM (Large Language Models) and RAG (Retrieval Augmented Generation) applications, aiming to develop powerful indexing engines. By introducing various advanced methods, it significantly reduces the time required to crawl domains and improves the efficiency of the retrieval process. HyperCrawl is part of HyperLLM, dedicated to building the future infrastructure for LLMs that require fewer computational resources and outperform existing models.

ILLA Cloud is an open-source low-code platform with a React component library, allowing you to build internal applications in minutes. It offers various pre-built components and database integrations for building AI tools, dashboards, management panels, and more. With features like an attractive user interface, real-time collaboration, connectivity to any data source, and customizable components, ILLA Cloud empowers you to build internal tools rapidly.