Showing 2738 open source projects for "hash-linux"

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  • 1
    Free LLM API resources

    Free LLM API resources

    A list of free LLM inference resources accessible via API

    Free LLM API resources repository curated by cheahjs is a community-driven index of free and open API endpoints, tools, datasets, runtimes, and utilities for working with large language models (LLMs) without cost-barriers. It collects a wide range of resources including hosted free-tier LLM APIs, documentation links, public model endpoints, open datasets useful for training or evaluation, tooling integrations, and examples showing how to interact with these services in real applications....
    Downloads: 5 This Week
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  • 2
    Claude Cognitive

    Claude Cognitive

    Persistent context and multi-instance coordination

    Claude Cognitive is an advanced memory and context-management extension designed to address the stateless limitations of Claude Code by giving the model a form of persistent “working memory” and multi-instance coordination. It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant...
    Downloads: 5 This Week
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  • 3
    SimpleMem

    SimpleMem

    SimpleMem: Efficient Lifelong Memory for LLM Agents

    SimpleMem is a lightweight memory-augmented model framework that helps developers build AI applications that retain long-term context and recall relevant information without overloading model context windows. It provides easy-to-use APIs for storing structured memory entries, querying those memories using semantic search, and retrieving context to augment prompt inputs for downstream processing. Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory...
    Downloads: 5 This Week
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  • 4
    UltraRAG

    UltraRAG

    Less Code, Lower Barrier, Faster Deployment

    UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. It...
    Downloads: 5 This Week
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  • 5
    Agent S

    Agent S

    Agent S: an open agentic framework that uses computers like a human

    ...Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines powerful foundation models (such as GPT-5) with grounding models like UI-TARS to translate visual inputs into precise executable actions. ...
    Downloads: 5 This Week
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  • 6
    DOLMA

    DOLMA

    Data and tools for generating and inspecting OLMo pre-training data

    DOLMA (Data Optimization and Learning for Model Alignment) is a framework designed to manage large-scale datasets for training and fine-tuning language models efficiently.
    Downloads: 4 This Week
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  • 7
    PaperAI

    PaperAI

    Semantic search and workflows for medical/scientific papers

    PaperAI is an open-source framework for searching and analyzing scientific papers, particularly useful for researchers looking to extract insights from large-scale document collections.
    Downloads: 4 This Week
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  • 8
    aisuite

    aisuite

    Simple, unified interface to multiple Generative AI providers

    Simple, unified interface to multiple Generative AI providers. aisuite makes it easy for developers to use multiple LLM through a standardized interface. Using an interface similar to OpenAI's, aisuite makes it easy to interact with the most popular LLMs and compare the results. It is a thin wrapper around Python client libraries and allows creators to seamlessly swap out and test responses from different LLM providers without changing their code. Today, the library is primarily focused on...
    Downloads: 5 This Week
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  • 9
    Taipy

    Taipy

    Turns Data and AI algorithms into production-ready web applications

    From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape....
    Downloads: 5 This Week
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  • 10
    Bytewax

    Bytewax

    Python Stream Processing

    Bytewax is a Python framework that simplifies event and stream processing. Because Bytewax couples the stream and event processing capabilities of Flink, Spark, and Kafka Streams with the friendly and familiar interface of Python, you can re-use the Python libraries you already know and love. Connect data sources, run stateful transformations, and write to various downstream systems with built-in connectors or existing Python libraries. Bytewax is a Python framework and Rust distributed...
    Downloads: 5 This Week
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  • 11
    PyBroker

    PyBroker

    Algorithmic Trading in Python with Machine Learning

    Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance.
    Downloads: 5 This Week
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  • 12
    Stable Baselines3

    Stable Baselines3

    PyTorch version of Stable Baselines

    Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch. It is the next major version of Stable Baselines. You can read a detailed presentation of Stable Baselines3 in the v1.0 blog post or our JMLR paper. These algorithms will make it easier for the research community and industry to replicate, refine, and identify new ideas, and will create good baselines to build projects on top of. We expect these tools will be used as a base around...
    Downloads: 5 This Week
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  • 13
    Alibi Detect

    Alibi Detect

    Algorithms for outlier, adversarial and drift detection

    Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. Both TensorFlow and PyTorch backends are supported for drift detection.
    Downloads: 4 This Week
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  • 14
    Python Client For NLP Cloud

    Python Client For NLP Cloud

    NLP Cloud serves high performance pre-trained or custom models for NER

    NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search,...
    Downloads: 5 This Week
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  • 15
    CTGAN

    CTGAN

    Conditional GAN for generating synthetic tabular data

    CTGAN is a collection of Deep Learning based synthetic data generators for single table data, which are able to learn from real data and generate synthetic data with high fidelity. If you're just getting started with synthetic data, we recommend installing the SDV library which provides user-friendly APIs for accessing CTGAN. The SDV library provides wrappers for preprocessing your data as well as additional usability features like constraints. When using the CTGAN library directly, you may...
    Downloads: 5 This Week
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  • 16
    OpenCLIP

    OpenCLIP

    An open source implementation of CLIP

    The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when...
    Downloads: 5 This Week
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  • 17
    PyTorch Forecasting

    PyTorch Forecasting

    Time series forecasting with PyTorch

    PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. A base model class that provides basic training of time series models along with...
    Downloads: 5 This Week
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  • 18
    BentoML

    BentoML

    Unified Model Serving Framework

    BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference...
    Downloads: 5 This Week
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  • 19
    openpilot

    openpilot

    Open source driver assistance system

    openpilot is an open-source driver assistance system designed to improve upon the existing driver assistance of most modern cars today. openpilot gives you Tesla Autopilot-like functionality with functions like Adaptive Cruise Control (ACC), Automated Lane Centering (ALC), Forward Collision Warning (FCW) and Lane Departure Warning (LDW). All these with just a push of a button. openpilot also includes a camera-based driver monitoring feature that alerts distracted and asleep drivers while it...
    Downloads: 5 This Week
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  • 20
    GLM-4

    GLM-4

    GLM-4 series: Open Multilingual Multimodal Chat LMs

    GLM-4 is a family of open models from ZhipuAI that spans base, chat, and reasoning variants at both 32B and 9B scales, with long-context support and practical local-deployment options. The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The...
    Downloads: 6 This Week
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  • 21
    MemPalace

    MemPalace

    The highest-scoring AI memory system ever benchmarked

    MemPalace is an open-source AI memory system designed to solve one of the most persistent limitations of large language models: the loss of context between sessions. Instead of relying on summarization or selective extraction like most memory tools, it takes a radically different approach by storing conversations in their entirety and making them retrievable through structured organization and semantic search. The system is inspired by the classical “memory palace” mnemonic technique,...
    Downloads: 5 This Week
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  • 22
    AI-Media2Doc

    AI-Media2Doc

    AI tool converting video/audio into structured documents instantly

    AI-Media2Doc is a web-based application that uses large language models to convert video and audio content into structured, readable documents in a single workflow. It is designed to transform multimedia inputs into formats such as knowledge notes, summaries, mind maps, and social-style articles, making content easier to review and reuse. AI-Media2Doc emphasizes privacy by processing media locally in the browser using WebAssembly-based ffmpeg, ensuring that original video files are not...
    Downloads: 5 This Week
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  • 23
    LoLLMs WEBUI

    LoLLMs WEBUI

    Local AI WebUI for running and managing large language models offlineA

    lollms-webui is a locally hosted web interface designed to run and manage large language models without relying on external services. It provides users with a centralized environment to interact with multiple AI models, making it suitable for experimentation, development, and personal use. lollms-webui emphasizes offline capability, allowing users to maintain privacy and control over their data while still accessing advanced AI features. It integrates model management tools that help users...
    Downloads: 5 This Week
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  • 24
    Dagger

    Dagger

    Containerized automation engine for programmable CI/CD workflows

    Dagger is an open source automation engine designed to build, test, and deliver software in a consistent and programmable way. It enables developers to define software delivery workflows using code instead of complex shell scripts or configuration files. Dagger executes tasks inside containers, ensuring that automation runs in identical environments across local machines, CI servers, or cloud infrastructure. Dagger provides a core execution engine and system API that orchestrates containers,...
    Downloads: 5 This Week
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  • 25
    Agent Behavior Monitoring

    Agent Behavior Monitoring

    The open source post-building layer for agents

    Agent Behavior Monitoring is an open-source framework designed to monitor, evaluate, and improve the behavior of AI agents operating in real or simulated environments. The system focuses on agent behavior monitoring by collecting interaction data and analyzing how agents perform across different scenarios and tasks. Developers can use the framework to observe agent actions in both online production environments and offline evaluation settings, making it useful for debugging and performance...
    Downloads: 5 This Week
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