Showing 2026 open source projects for "pam-python"

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  • 1
    Watermark Anything

    Watermark Anything

    Official implementation of Watermark Anything with Localized Messages

    Watermark Anything (WAM) is an advanced deep learning framework for embedding and detecting localized watermarks in digital images. Developed by Facebook Research, it provides a robust, flexible system that allows users to insert one or multiple watermarks within selected image regions while maintaining visual quality and recoverability. Unlike traditional watermarking methods that rely on uniform embedding, WAM supports spatially localized watermarks, enabling targeted protection of...
    Downloads: 1 This Week
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  • 2
    SlowFast

    SlowFast

    Video understanding codebase from FAIR for reproducing video models

    SlowFast is a video understanding framework that captures both spatial semantics and temporal dynamics efficiently by processing video frames at two different temporal resolutions. The slow pathway encodes semantic context by sampling frames sparsely, while the fast pathway captures motion and fine temporal cues by operating on densely sampled frames with fewer channels. Together, these two pathways complement each other, allowing the network to model both appearance and motion without...
    Downloads: 1 This Week
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  • 3
    DeepSeek VL

    DeepSeek VL

    Towards Real-World Vision-Language Understanding

    DeepSeek-VL is DeepSeek’s initial vision-language model that anchors their multimodal stack. It enables understanding and generation across visual and textual modalities—meaning it can process an image + a prompt, answer questions about images, caption, classify, or reason about visuals in context. The model is likely used internally as the visual encoder backbone for agent use cases, to ground perception in downstream tasks (e.g. answering questions about a screenshot). The repository...
    Downloads: 1 This Week
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  • 4
    Semantic Router

    Semantic Router

    Superfast AI decision making and processing of multi-modal data

    Semantic Router is a superfast decision-making layer for your LLMs and agents. Rather than waiting for slow, unreliable LLM generations to make tool-use or safety decisions, we use the magic of semantic vector space — routing our requests using semantic meaning. Combining LLMs with deterministic rules means we can be confident that our AI systems behave as intended. Cramming agent tools into the limited context window is expensive, slow, and fundamentally limited. Semantic Router enables...
    Downloads: 1 This Week
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    Flower

    Flower

    Flower: A Friendly Federated Learning Framework

    A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language. Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new...
    Downloads: 1 This Week
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  • 6
    garak

    garak

    Developers and anyone seeking an LLM solution to scan for vulnerabilit

    garak checks if an LLM can be made to fail in a way we don't want. garak probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses. garak's a free tool, we love developing it and are always interested in adding functionality to support applications. garak is a command-line tool, it's developed in Linux and OSX. Just grab it from PyPI and you should be good to go. The standard pip version of garak is updated...
    Downloads: 1 This Week
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  • 7
    LangChain-Chatchat

    LangChain-Chatchat

    Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge

    LangChain-Chatchat (formerly Langchain-ChatGLM): A local knowledge base question answering application implementation based on large language models such as Langchain and ChatGLM. The knowledge base information of the current project is stored in the database, please initialize the database before running the project officially (we strongly recommend that you back up your knowledge files before performing operations). Relying on the open-source LLM and Embedding models supported by this...
    Downloads: 1 This Week
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  • 8
    Label Sleuth

    Label Sleuth

    Open source no-code system for text annotation and building of text

    An open-source no-code system for text annotation and building text classifiers. No AI knowledge needed. From task definition to working model in just a few hours! While domain experts label their data, Label Sleuth automatically trains in the background-appropriate machine learning models. To avoid wasted labeling effort, Label Sleuth employs active learning techniques to guide the user in what they should be labeled next. Domain experts can quickly start labeling their data through an...
    Downloads: 1 This Week
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  • 9
    MindsDB

    MindsDB

    Making Enterprise Data Intelligent and Responsive for AI

    MindsDB is an AI data solution that enables humans, AI, agents, and applications to query data in natural language and SQL, and get highly accurate answers across disparate data sources and types. MindsDB connects to diverse data sources and applications, and unifies petabyte-scale structured and unstructured data. Powered by an industry-first cognitive engine that can operate anywhere (on-prem, VPC, serverless), it empowers both humans and AI with highly informed decision-making...
    Downloads: 3 This Week
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  • 10
    openctp

    openctp

    Provides CTP stock options and Zhongtai Securities XTP

    ...The project offers a comprehensive simulation environment similar to SimNow that supports futures, options, A share stocks, funds, bonds, and stock options, and even extends to Hong Kong and US markets. In addition to the core library, openctp supplies Python bindings for CTPAPI and stock options APIs, making it easier to build strategies, tools, and analytics in Python. It also develops full featured and lightweight trading clients like TickTrader, TickTraderMini, and ViTrader, which support multiple desks and markets.
    Downloads: 0 This Week
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  • 11
    Gemma

    Gemma

    Gemma open-weight LLM library, from Google DeepMind

    Gemma, developed by Google DeepMind, is a family of open-weights large language models (LLMs) built upon the research and technology behind Gemini. This repository provides the official implementation of the Gemma PyPI package, a JAX-based library that enables users to load, interact with, and fine-tune Gemma models. The framework supports both text and multi-modal input, allowing natural language conversations that incorporate visual content such as images. It includes APIs for...
    Downloads: 0 This Week
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  • 12
    airda

    airda

    airda(Air Data Agent

    airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes.
    Downloads: 0 This Week
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  • 13
    Griptape

    Griptape

    Python framework for AI workflows and pipelines with chain of thought

    The Griptape framework provides developers with the ability to create AI systems that operate across two dimensions: predictability and creativity. For predictability, Griptape enforces structures like sequential pipelines, DAG-based workflows, and long-term memory. To facilitate creativity, Griptape safely prompts LLMs with tools (keeping output data off prompt by using short-term memory), which connects them to external APIs and data stores. The framework allows developers to transition...
    Downloads: 0 This Week
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  • 14
    NannyML

    NannyML

    Detecting silent model failure. NannyML estimates performance

    NannyML is an open-source python library that allows you to estimate post-deployment model performance (without access to targets), detect data drift, and intelligently link data drift alerts back to changes in model performance. Built for data scientists, NannyML has an easy-to-use interface, and interactive visualizations, is completely model-agnostic, and currently supports all tabular classification use cases.
    Downloads: 0 This Week
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  • 15
    Pytorch-toolbelt

    Pytorch-toolbelt

    PyTorch extensions for fast R&D prototyping and Kaggle farming

    A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images.
    Downloads: 0 This Week
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  • 16
    PyTorch Geometric Temporal

    PyTorch Geometric Temporal

    Spatiotemporal Signal Processing with Neural Machine Learning Models

    The library consists of various dynamic and temporal geometric deep learning, embedding, and Spatio-temporal regression methods from a variety of published research papers. Moreover, it comes with an easy-to-use dataset loader, train-test splitter and temporal snaphot iterator for dynamic and temporal graphs. The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic...
    Downloads: 0 This Week
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  • 17
    PySyft

    PySyft

    Data science on data without acquiring a copy

    Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data...
    Downloads: 0 This Week
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  • 18
    DGL

    DGL

    Python package built to ease deep learning on graph

    Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers....
    Downloads: 0 This Week
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  • 19
    LLM Action

    LLM Action

    Technical principles related to large models

    LLM-Action is a knowledge/tutorial/repository that shares principles, techniques, and real-world experience related to large language models (LLMs), focusing on LLM engineering, deployment, optimization, inference, compression, and tooling. It organizes content in domains like training, inference, compression, alignment, evaluation, pipelines, and applications. Sections covering infrastructure, engineering, and deployment. Repository templates, sample code, and resource links. Articles/code...
    Downloads: 0 This Week
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  • 20
    Notte

    Notte

    Opensource browser using agents

    Notte is an open-source browser framework that enables the development and deployment of web-based AI agents. It introduces a perception layer that transforms web pages into structured, navigable maps described in natural language, allowing agents to interact with the internet more effectively. Notte is designed for building scalable and efficient browser-based AI applications.
    Downloads: 0 This Week
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  • 21
    LightZero

    LightZero

    [NeurIPS 2023 Spotlight] LightZero

    LightZero is an efficient, scalable, and open-source framework implementing MuZero, a powerful model-based reinforcement learning algorithm that learns to predict rewards and transitions without explicit environment models. Developed by OpenDILab, LightZero focuses on providing a highly optimized and user-friendly platform for both academic research and industrial applications of MuZero and similar algorithms.
    Downloads: 0 This Week
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  • 22
    EvoTorch

    EvoTorch

    Advanced evolutionary computation library built on top of PyTorch

    EvoTorch is an evolutionary optimization framework built on top of PyTorch, developed by NNAISENSE. It is designed for large-scale optimization problems, particularly those that require evolutionary algorithms rather than gradient-based methods.
    Downloads: 0 This Week
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  • 23
    Gymnasium

    Gymnasium

    An API standard for single-agent reinforcement learning environments

    Gymnasium is a fork of OpenAI Gym, maintained by the Farama Foundation, that provides a standardized API for reinforcement learning environments. It improves upon Gym with better support, maintenance, and additional features while maintaining backward compatibility.
    Downloads: 0 This Week
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  • 24
    PaLM + RLHF - Pytorch

    PaLM + RLHF - Pytorch

    Implementation of RLHF (Reinforcement Learning with Human Feedback)

    PaLM-rlhf-pytorch is a PyTorch implementation of Pathways Language Model (PaLM) with Reinforcement Learning from Human Feedback (RLHF). It is designed for fine-tuning large-scale language models with human preference alignment, similar to OpenAI’s approach for training models like ChatGPT.
    Downloads: 0 This Week
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  • 25
    OpenRLHF

    OpenRLHF

    An Easy-to-use, Scalable and High-performance RLHF Framework

    OpenRLHF is an easy-to-use, scalable, and high-performance framework for Reinforcement Learning with Human Feedback (RLHF). It supports various training techniques and model architectures.
    Downloads: 0 This Week
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