Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 48

Showing 2744 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"

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  • 1
    PRIME

    PRIME

    Scalable RL solution for advanced reasoning of language models

    ...PRIME provides training pipelines, datasets, and experimental infrastructure that allow researchers to train models with reinforcement learning tailored for reasoning improvement. The framework also includes data preprocessing utilities and example datasets such as mathematical reasoning tasks that are well suited for process-based reward signals.
    Downloads: 1 This Week
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  • 2
    Huatuo-Llama-Med-Chinese

    Huatuo-Llama-Med-Chinese

    Instruction-tuning LLM with Chinese Medical Knowledge

    ...The goal of the project is to improve the reliability and domain expertise of language models when answering medical questions or assisting with healthcare-related tasks. By combining domain-specific training data with instruction-tuning techniques, the project produces models capable of generating more accurate medical responses than general-purpose models.
    Downloads: 1 This Week
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  • 3
    PowerInfer

    PowerInfer

    High-speed Large Language Model Serving for Local Deployment

    ...This hybrid execution strategy significantly reduces memory bottlenecks and improves overall inference speed. PowerInfer incorporates specialized algorithms and sparse operators to manage neuron activation patterns and minimize data transfers between hardware components. As a result, it enables powerful language models to run on consumer hardware while achieving performance comparable to more expensive server-grade systems.
    Downloads: 1 This Week
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  • 4
    Agent SOP

    Agent SOP

    Natural language workflows for AI agents

    ...It defines reusable SOP templates that agents can instantiate with context-specific parameters, allowing organizations to codify best practices for customer support, data processing, document workflows, or incident response. The framework supports monitoring and state tracking, so external systems can observe progress, intervene if necessary, and log outcomes for compliance or auditing. Integrations with common messaging and task orchestration systems enable SOP agents to interact with email, ticket queues, and databases as part of their workflows.
    Downloads: 1 This Week
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    ERP Software To Simplify Your Manufacturing

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  • 5
    Mem0

    Mem0

    The Memory layer for AI Agents

    ...It remembers user preferences, adapts to individual needs, and continuously improves over time. Key features include enhancing future conversations by building smarter AI that learns from every interaction, reducing LLM costs by up to 80% through intelligent data filtering, delivering more accurate and personalized AI outputs by leveraging historical context, and offering easy integration compatible with platforms like OpenAI and Claude. Mem0 is perfect for projects such as customer support, where chatbots remember past interactions to reduce repetition and speed up resolution times; personal AI companions that recall preferences and past conversations for more meaningful interactions; AI agents that learn from each interaction to become more personalized and effective over time.
    Downloads: 1 This Week
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  • 6
    BISHENG

    BISHENG

    BISHENG is an open LLM devops platform for next generation apps

    BISHENG is an open LLM application DevOps platform, focusing on enterprise scenarios. It has been used by a large number of industry-leading organizations and Fortune 500 companies. "Bi Sheng" was the inventor of movable type printing, which played a vital role in promoting the transmission of human knowledge. We hope that BISHENG can also provide strong support for the widespread implementation of intelligent applications. Everyone is welcome to participate.
    Downloads: 1 This Week
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  • 7
    PyG

    PyG

    Graph Neural Network Library for PyTorch

    PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support, distributed graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. ...
    Downloads: 1 This Week
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  • 8
    LeWorldModel

    LeWorldModel

    Official code base for LeWorldModel: Stable End-to-End Joint-Embedding

    ...The project emphasizes a lightweight design, minimizing resource usage while maintaining responsiveness and stability. It is highly configurable through source code or configuration files, allowing users to tailor behavior, keybindings, and layouts to their preferences. le-wm is intended for users who prefer keyboard-driven workflows and a distraction-free desktop environment. Its architecture avoids unnecessary complexity, making it easy to understand, modify, and extend.
    Downloads: 0 This Week
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  • 9
    Gemma in PyTorch

    Gemma in PyTorch

    The official PyTorch implementation of Google's Gemma models

    gemma_pytorch provides the official PyTorch reference for running and fine-tuning Google’s Gemma family of open models. It includes model definitions, configuration files, and loading utilities for multiple parameter scales, enabling quick evaluation and downstream adaptation. The repository demonstrates text generation pipelines, tokenizer setup, quantization paths, and adapters for low-rank or parameter-efficient fine-tuning. Example notebooks walk through instruction tuning and evaluation so teams can benchmark and iterate rapidly. ...
    Downloads: 0 This Week
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  • 10
    Code Review GPT

    Code Review GPT

    Your personal code reviewer powered by LLMs

    Code Review GPT uses Large Language Models to review code in your CI/CD pipeline. It helps streamline the code review process by providing feedback on code that may have issues or areas for improvement. Code Review GPT is in alpha and should be used for fun only. It may provide useful feedback but please check any suggestions thoroughly.
    Downloads: 0 This Week
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  • 11
    PyTorch Image Models

    PyTorch Image Models

    The largest collection of PyTorch image encoders / backbones

    timm (PyTorch Image Models) is a premier library hosting a vast collection of state-of-the-art image classification models and backbones such as ResNet, EfficientNet, NFNet, Vision Transformer, ConvNeXt, and more. Created by Ross Wightman and now maintained by Hugging Face, it includes pretrained weights, data loaders, augmentations, optimizers, schedulers, and reference scripts for training, evaluation, inference, and model export. It's an essential toolkit for vision research and production workflows.
    Downloads: 0 This Week
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  • 12
    HDBSCAN

    HDBSCAN

    A high performance implementation of HDBSCAN clustering

    ...In practice this means that HDBSCAN returns a good clustering straight away with little or no parameter tuning -- and the primary parameter, minimum cluster size, is intuitive and easy to select. HDBSCAN is ideal for exploratory data analysis; it's a fast and robust algorithm that you can trust to return meaningful clusters (if there are any).
    Downloads: 0 This Week
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  • 13
    dtreeviz

    dtreeviz

    Python library for decision tree visualization & model interpretation

    ...Decision trees are the fundamental building block of gradient boosting machines and Random Forests(tm), probably the two most popular machine learning models for structured data. Visualizing decision trees is a tremendous aid when learning how these models work and when interpreting models. The visualizations are inspired by an educational animation by R2D3; A visual introduction to machine learning. Please see How to visualize decision trees for deeper discussion of our decision tree visualization library and the visual design decisions we made.
    Downloads: 0 This Week
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  • 14
    imodelsX

    imodelsX

    Interpretable prompting and models for NLP

    Interpretable prompting and models for NLP (using large language models). Generates a prompt that explains patterns in data (Official) Explain the difference between two distributions. Find a natural-language prompt using input-gradients. Fit a better linear model using an LLM to extract embeddings. Fit better decision trees using an LLM to expand features. Finetune a single linear layer on top of LLM embeddings. Use these just a like a sci-kit-learn model.
    Downloads: 0 This Week
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  • 15
    MiniMax-MCP

    MiniMax-MCP

    Official MiniMax Model Context Protocol (MCP) server

    ...The server is written in Python and distributed under the MIT license, with a pyproject.toml and uv-based workflow that makes installation and execution reproducible. Configuration is handled through JSON files that tell MCP clients how to launch the server (typically via uvx minimax-mcp) and which environment variables to use for the API key, host, and output directory. The README carefully explains region-specific API hosts for global and mainland users to avoid invalid-key errors, and documents both local stdio transport and SSE-based network transport modes.
    Downloads: 1 This Week
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  • 16
    Xianyu Intelligent Monitor Bot

    Xianyu Intelligent Monitor Bot

    AI tool for real-time monitoring and analysis of Goofish listings

    ...It combines browser automation with AI-based analysis to automatically search, collect, and evaluate newly posted items that match a user’s purchase criteria. It uses Playwright to simulate real user interactions with the marketplace, allowing the system to retrieve product data and track updates in near real time. ai-goofish-monitor can run multiple monitoring tasks simultaneously, each configured with specific keywords, price ranges, and filtering conditions. A built-in web management interface allows users to create tasks, review results, and manage monitoring rules without relying solely on command line tools. ...
    Downloads: 1 This Week
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  • 17
    Flock

    Flock

    Flock is a workflow-based low-code platform for building chatbots

    Flock is a workflow-based low-code platform designed for building AI applications such as chatbots, retrieval-augmented generation systems, and multi-agent workflows. The platform uses a visual workflow architecture where different nodes represent processing steps such as input processing, model inference, retrieval operations, and tool execution. Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on...
    Downloads: 1 This Week
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  • 18
    Aden Hive

    Aden Hive

    Outcome driven agent development framework that evolves

    ...Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can capture failure data, evolve automatically to meet their success criteria, and redeploy without constant manual intervention, delivering continual improvement over time. The framework also includes human-in-the-loop nodes, credential management, cost and budget controls, and real-time observability so teams can monitor execution and intervene as needed. ...
    Downloads: 1 This Week
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  • 19
    Simple StyleGan2 for Pytorch

    Simple StyleGan2 for Pytorch

    Simplest working implementation of Stylegan2

    Simple Pytorch implementation of Stylegan2 that can be completely trained from the command-line, no coding needed. You will need a machine with a GPU and CUDA installed. You can also specify the location where intermediate results and model checkpoints should be stored. You can increase the network capacity (which defaults to 16) to improve generation results, at the cost of more memory. By default, if the training gets cut off, it will automatically resume from the last checkpointed file....
    Downloads: 1 This Week
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  • 20
    TensorFlow Serving

    TensorFlow Serving

    Serving system for machine learning models

    ...It deals with the inference aspect of machine learning, taking models after training and managing their lifetimes, providing clients with versioned access via a high-performance, reference-counted lookup table. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data. The easiest and most straight-forward way of using TensorFlow Serving is with Docker images. We highly recommend this route unless you have specific needs that are not addressed by running in a container. In order to serve a Tensorflow model, simply export a SavedModel from your Tensorflow program. SavedModel is a language-neutral, recoverable, hermetic serialization format that enables higher-level systems and tools to produce, consume, and transform TensorFlow models.
    Downloads: 1 This Week
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  • 21
    ML.NET

    ML.NET

    Open source and cross-platform machine learning framework for .NET

    ...These tools use Automated ML (AutoML), a cutting edge technology that automates the process of building best performing models for your Machine Learning scenario. All you have to do is load your data, and AutoML takes care of the rest of the model building process. ML.NET has been designed as an extensible platform so that you can consume other popular ML frameworks (TensorFlow, ONNX, Infer.NET, and more) and have access to even more machine learning scenarios, like image classification, object detection, and more.
    Downloads: 1 This Week
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  • 22
    goodsKill

    goodsKill

    Microservices-based flash sale system for high-concurrency testing

    ...It provides a unified API for testing high-concurrency seckill scenarios while demonstrating modern backend architecture patterns. goodsKill integrates key components such as Nacos for service discovery and configuration, Redis and MongoDB for data handling, and Kafka or RabbitMQ for messaging. It supports distributed transactions, database sharding, and multiple concurrency control strategies including distributed locks and message queues. It includes modular services like gateway, authentication, order management, and seckill processing, along with a Vue 3-based admin UI. ...
    Downloads: 1 This Week
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  • 23
    autoresearch-macos

    autoresearch-macos

    AI agents running research on single-GPU nanochat training

    ...It is designed to operate efficiently within macOS environments, making it accessible for developers working outside traditional high-performance GPU clusters. The project typically includes components such as data preparation scripts, a training loop, and an instruction file that guides the agent’s behavior. By automating experimentation and optimization, it allows continuous improvement without manual intervention, effectively turning research into a self-improving process.
    Downloads: 0 This Week
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  • 24
    BestBlogs

    BestBlogs

    A collection of top programming

    ...The platform focuses on curating content based on relevance, quality, and usefulness rather than simply indexing large volumes of information, making it particularly useful for developers, researchers, and knowledge seekers. It typically integrates automated data collection and filtering mechanisms to gather blog posts from multiple sources, then categorizes and ranks them to improve discoverability. The system is designed to be lightweight and customizable, allowing developers to adapt it for specific niches, industries, or content strategies. BestBlogs can also serve as a foundation for building content recommendation systems, knowledge hubs, or developer portals.
    Downloads: 0 This Week
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  • 25
    PilottAI

    PilottAI

    Python framework for building scalable multi-agent systems

    pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers.
    Downloads: 0 This Week
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