Search Results for "waydroid-linux" - Page 8
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Showing 404 open source projects for "waydroid-linux"
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EmoLLM
Pre & Post-training & Dataset & Evaluation & Depoly & RAG
EmoLLM is an open-source family of large language models focused on mental health support and counseling-oriented interactions. The project is designed to help users through mental health conversations and has been fine-tuned from existing instruction-following LLMs rather than built as a base model from scratch. Its repository includes multiple model variants and training configurations spanning several underlying model families, including InternLM, Qwen, DeepSeek, Mixtral, LLaMA, and... -
2
yt-fts
Search all of YouTube from the command line
yt-fts, short for YouTube Full Text Search, is an open-source command-line tool that enables users to search the spoken content of YouTube videos by indexing their subtitles. The program automatically downloads subtitles from a specified YouTube channel using the yt-dlp utility and stores them in a local SQLite database. Once indexed, users can perform full-text searches across all transcripts to quickly locate keywords or phrases mentioned within the videos. The tool returns search results... -
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HolmesGPT
CNCF Sandbox Project
HolmesGPT is an open-source AI agent designed to help DevOps and site reliability engineering teams diagnose and resolve production incidents. The system aggregates signals from observability tools such as logs, metrics, alerts, and distributed traces, then analyzes them using large language models to identify potential root causes. Rather than requiring engineers to manually correlate large volumes of monitoring data, HolmesGPT automatically synthesizes evidence and presents explanations in... -
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TokenCost
Easy token price estimates for 400+ LLMs. TokenOps
TokenCost is an open-source developer utility designed to estimate the cost of using large language model APIs by calculating token usage and translating it into real monetary values. The tool focuses on helping developers understand how much their prompts and generated completions cost when interacting with commercial AI models. It works by counting tokens in prompts and responses before or after sending requests and then applying pricing information associated with different models. This... -
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LLMs-Zero-to-Hero
From nobody to big model (LLM) hero
LLMs-Zero-to-Hero is an open-source educational project designed to guide learners through the complete process of understanding and building large language models from the ground up. The repository presents a structured learning pathway that begins with fundamental concepts in machine learning and progresses toward advanced topics such as model pre-training, fine-tuning, and deployment. Rather than relying entirely on existing frameworks, the project encourages readers to implement... -
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LlamaDeploy
Deploy your agentic worfklows to production
llama_deploy is an open-source framework designed to simplify the deployment and productionization of agent-based AI workflows built with the LlamaIndex ecosystem. The project provides an asynchronous architecture that allows developers to deploy complex multi-agent workflows as scalable microservices. It enables teams to move from experimental prototypes to production systems with minimal changes to existing LlamaIndex code, making it easier to operationalize AI agents. The system supports... -
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MoBA
MoBA: Mixture of Block Attention for Long-Context LLMs
MoBA, short for Mixture of Block Attention, is an open-source research implementation of a novel attention mechanism designed to improve the efficiency of large language models processing extremely long contexts. The architecture adapts ideas from Mixture-of-Experts networks and applies them directly to the attention mechanism of transformer models. Instead of forcing each token to attend to every other token in the sequence, MoBA divides the context into blocks and dynamically routes... -
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AI Engineering Academy
Mastering Applied AI, One Concept at a Time
AI-Engineering.academy is a community-driven educational repository that organizes practical knowledge and learning paths for applied AI engineering. The project aims to make complex AI concepts accessible by structuring them into progressive learning modules covering topics such as prompt engineering, retrieval-augmented generation, LLM deployment, and AI agents. Rather than focusing purely on theoretical explanations, the repository emphasizes hands-on understanding of how modern AI... -
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OM1
Modular AI runtime for robots
OM1 is an open-source AI platform designed to build autonomous agents capable of interacting with digital environments and completing complex tasks. The project focuses on creating a modular architecture where language models can coordinate with external tools, APIs, and knowledge sources to accomplish multi-step objectives. Instead of operating as simple conversational systems, OM1 agents can plan actions, retrieve information, and execute tasks across different services. The framework... -
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10
how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
how-to-optim-algorithm-in-cuda is an open educational repository focused on teaching developers how to optimize algorithms for high-performance execution on GPUs using CUDA. The project combines technical notes, code examples, and practical experiments that demonstrate how common computational kernels can be optimized to improve speed and memory efficiency. Instead of presenting only theoretical explanations, the repository includes hand-written CUDA implementations of fundamental operations... -
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SwanLab
An open-source, modern-design AI training tracking and visualization
SwanLab is an open-source experiment tracking and visualization platform designed to help machine learning engineers monitor, compare, and analyze the training of artificial intelligence models. The tool records training metrics, hyperparameters, model outputs, and experiment configurations so that developers can easily understand how different experiments perform over time. It provides a modern user interface for visualizing results, enabling teams to compare runs, track model performance... -
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LMOps
General technology for enabling AI capabilities w/ LLMs and MLLMs
LMOps is a research initiative and open-source toolkit focused on the development and operational management of AI applications built with large language models and generative AI systems. The project explores the technologies and methodologies required to move foundation models from research environments into production-grade AI products. It includes experimental tools and frameworks that help developers optimize prompts, design workflows for generative models, and manage the lifecycle of... -
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Integuru v0
The first AI agent that builds permissionless integrations
Integuru is an open-source AI agent designed to automatically create integrations between software platforms by reverse-engineering their internal APIs. Instead of relying on official developer documentation or publicly available APIs, the system analyzes network traffic generated by user interactions within a web application. Developers capture browser requests and authentication data, which the agent then uses to infer the structure of the platform’s internal API endpoints. Based on this... -
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CodeGen
Open-source model for program synthesis
CodeGen is a family of open-source large language models designed specifically for program synthesis and code generation tasks. Developed by Salesforce Research, the models are trained on large datasets containing both natural language and programming language content. This allows them to translate natural language descriptions into functional code across a variety of programming languages. CodeGen supports multi-turn program synthesis, meaning it can generate complex programs through a... -
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UFO³
Weaving the Digital Agent Galaxy
UFO is an open-source framework developed by Microsoft for building intelligent agents that automate interactions with graphical user interfaces on the Windows operating system. The system allows users to issue natural language instructions that are translated into automated actions across multiple desktop applications. Using a dual-agent architecture, the framework analyzes both visual interface elements and system control structures in order to understand how applications should be... -
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Llama-Chinese
Llama Chinese community, real-time aggregation
Llama-Chinese is an open source community initiative focused on adapting and improving Meta’s LLaMA language models for Chinese language applications. The project aggregates datasets, research resources, tutorials, and tools that help developers train and fine-tune LLaMA-based models with Chinese linguistic capabilities. It also provides optimized versions of LLaMA models trained on large-scale Chinese datasets to improve performance in tasks such as translation, summarization, and... -
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WeClone
One-stop solution for creating your digital avatar from chat history
WeClone is an open source AI project designed to replicate a person’s conversational style and personality by training models on chat history data. The system analyzes message patterns, linguistic style, and contextual behavior in order to generate responses that resemble the original user’s communication style. It is intended primarily as an experimental exploration of digital personality modeling and conversational AI personalization. By processing large volumes of conversation data,... -
18
Vanna 2.0
Chat with your SQL database
Vanna is an open-source Python framework that enables natural language interaction with databases by converting user questions into executable SQL queries using large language models. The framework uses a retrieval-augmented generation architecture that learns from database schemas, documentation, and past query examples to generate accurate queries tailored to a specific dataset. Vanna can be integrated into many environments, including notebooks, web applications, messaging platforms, and... -
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Happy-LLM
Large Language Model Principles and Practice Tutorial from Scratch
Happy-LLM is an open-source educational project created by the Datawhale AI community that provides a structured and comprehensive tutorial for understanding and building large language models from scratch. The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer... -
20
Reader 3
Quick illustration of how one can easily read books together with LLMs
This project is a minimalist, self-hosted EPUB reader designed to help users browse and read EPUB books one chapter at a time through a lightweight local server, making it especially easy to extract or work with chapters in external tools like large language models. It was created primarily as a simple demonstration of how to combine local book reading with LLM workflows without heavy dependencies or complicated setup, and it runs with just a small Python script and a basic HTTP server. The... -
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HN Time Capsule
Analyzing Hacker News discussions from a decade ago in hindsight
HN Time Capsule is a creative and nostalgic project that captures and preserves snapshots of Hacker News content over time, providing a historical look at how topics, discussions, and popular threads have evolved. Rather than functioning like a live aggregator, it stores periodic captures of posts and comments, creating a time capsule that lets researchers, enthusiasts, and historians trace changes in sentiment, technology trends, and community priorities across different eras of the Hacker... -
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Engram
A New Axis of Sparsity for Large Language Models
Engram is a high-performance embedding and similarity search library focused on making retrieval-augmented workflows efficient, scalable, and easy to adopt by developers building search, recommendation, or semantic matching systems. It provides utilities to generate embeddings from text or other structured data, index them using efficient approximate nearest neighbor algorithms, and perform real-time similarity queries even on large corpora. Engineered with speed and memory efficiency in... -
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llm.c
LLM training in simple, raw C/CUDA
llm.c is a minimalist, systems-level implementation of a small transformer-based language model in C that prioritizes clarity and educational value. By stripping away heavy frameworks, it exposes the core math and memory flows of embeddings, attention, and feed-forward layers. The code illustrates how to wire forward passes, losses, and simple training or inference loops with direct control over arrays and buffers. Its compact design makes it easy to trace execution, profile hotspots, and... -
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Ling
Ling is a MoE LLM provided and open-sourced by InclusionAI
Ling is a Mixture-of-Experts (MoE) large language model (LLM) provided and open-sourced by inclusionAI. The project offers different sizes (Ling-lite, Ling-plus) and emphasizes flexibility and efficiency: being able to scale, adapt expert activation, and perform across a range of natural language/reasoning tasks. Example scripts, inference pipelines, and documentation. The codebase includes inference, examples, models, documentation, and model download infrastructure. As more developers and... -
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. It is intended to facilitate reproducible RL training on reasoning / agentic tasks,...