Showing 527 open source projects for "python user interface"

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  • 1
    Guardrails

    Guardrails

    Adding guardrails to large language models

    Guardrails is a Python package that lets a user add structure, type and quality guarantees to the outputs of large language models (LLMs). At the heart of Guardrails is the rail spec. rail is intended to be a language-agnostic, human-readable format for specifying structure and type information, validators and corrective actions over LLM outputs. We create a RAIL spec to describe the expected structure and types of the LLM output, the quality criteria for the output to be considered valid...
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  • 2
    AgentForge

    AgentForge

    Extensible AGI Framework

    AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications.
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  • 3
    OpenCompass

    OpenCompass

    OpenCompass is an LLM evaluation platform

    Just like a compass guides us on our journey, OpenCompass will guide you through the complex landscape of evaluating large language models. With its powerful algorithms and intuitive interface, OpenCompass makes it easy to assess the quality and effectiveness of your NLP models. OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Pre-support for 20+ HuggingFace and API models, a model evaluation...
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  • 4
    Argilla

    Argilla

    The open-source data curation platform for LLMs

    ... libraries without implementing any specific interface. Most annotation tools treat data collection as a one-off activity at the beginning of each project. In real-world projects, data collection is a key activity of the iterative process of ML model development. Once a model goes into production, you want to monitor and analyze its predictions, and collect more data to improve your model over time. Argilla is designed to close this gap, enabling you to iterate as much as you need.
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  • 5
    zvt

    zvt

    Modular quant framework

    .... The core concept of the system is visual, and the name of the interface corresponds to it one-to-one, so it is also uniform and extensible. You can write and run the strategy in your favorite ide, and then view its related targets, factor, signal and performance on the UI. Once you are familiar with the core concepts of the system, you can apply it to any target in the market.
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  • 6
    MODMAIL

    MODMAIL

    A feature rich discord Modmail bot

    Modmail is similar to Reddit's Modmail, both in functionality and purpose. It serves as a shared inbox for server staff to communicate with their users in a seamless way. This bot is free for everyone and always will be. If you like this project and would like to show your appreciation, you can support us on Patreon, cool benefits included! When a member sends a direct message to the bot, Modmail will create a channel or "thread" into a designated category. All further DM messages will...
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  • 7
    PyTorch Ignite

    PyTorch Ignite

    Library to help with training and evaluating neural networks

    ..., simple function, class method, etc. Thus, we do not require to inherit from an interface and override its abstract methods which could unnecessarily bulk up your code and its complexity. Extremely simple engine and event system. Out-of-the-box metrics to easily evaluate models. Built-in handlers to compose training pipeline, save artifacts and log parameters and metrics.
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  • 8
    Norfair

    Norfair

    Lightweight Python library for adding real-time multi-object tracking

    Norfair is a customizable lightweight Python library for real-time multi-object tracking. Using Norfair, you can add tracking capabilities to any detector with just a few lines of code. Any detector expressing its detections as a series of (x, y) coordinates can be used with Norfair. This includes detectors performing tasks such as object or keypoint detection. It can easily be inserted into complex video processing pipelines to add tracking to existing projects. At the same time...
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  • 9
    ktrain

    ktrain

    ktrain is a Python library that makes deep learning AI more accessible

    ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines...
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  • 10
    Haiku

    Haiku

    JAX-based neural network library

    ... DeepMind. It preserves Sonnet’s module-based programming model for state management while retaining access to JAX’s function transformations. Haiku can be expected to compose with other libraries and work well with the rest of JAX. Similar to Sonnet modules, Haiku modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs.
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  • 11
    MiniMind

    MiniMind

    Train a 26M-parameter GPT from scratch in just 2h

    minimind is a framework that enables users to train a 26-million-parameter GPT (Generative Pre-trained Transformer) model from scratch in approximately two hours. It provides a streamlined process for data preparation, model training, and evaluation, making it accessible for individuals and organizations to develop their own language models without extensive computational resources.
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  • 12
    RA.Aid

    RA.Aid

    Develop software autonomously

    RA.Aid is an AI-powered assistant designed to enhance the efficiency of software development workflows. It integrates seamlessly with various development environments, providing intelligent code suggestions, automated documentation generation, and real-time error detection. By leveraging advanced machine learning models, RA.Aid aims to reduce development time and improve code quality.​
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  • 13
    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.
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  • 14
    XAgent

    XAgent

    An Autonomous LLM Agent for Complex Task Solving

    XAgent is an AI-driven autonomous agent framework capable of handling multi-step tasks across different domains. It enables AI agents to perform decision-making, task planning, and self-learning based on user-defined objectives, making it ideal for automation and research applications.
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  • 15
    Gorilla CLI

    Gorilla CLI

    LLMs for your CLI

    Gorilla CLI powers your command-line interactions with a user-centric tool. Simply state your objective, and Gorilla CLI will generate potential commands for execution. Gorilla today supports ~1500 APIs, including Kubernetes, AWS, GCP, Azure, GitHub, Conda, Curl, Sed, and many more. No more recalling intricate CLI arguments.
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  • 16
    Cherche

    Cherche

    Neural Search

    ... is fully compatible with the collaborative filtering library Implicit. It is advantageous if you have a history associated with users and you want to retrieve / re-rank documents based on user preferences.
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  • 17
    Sonnet

    Sonnet

    TensorFlow-based neural network library

    Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already...
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  • 18
    Haiku Sonnet for JAX

    Haiku Sonnet for JAX

    JAX-based neural network library

    ..., and a simple function transformation, hk.transform. hk.Modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs. hk.transform turns functions that use these object-oriented, functionally "impure" modules into pure functions that can be used with jax.jit, jax.grad, jax.pmap, etc.
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  • 19
    Core ML Tools

    Core ML Tools

    Core ML tools contain supporting tools for Core ML model conversion

    Use Core ML Tools (coremltools) to convert machine learning models from third-party libraries to the Core ML format. This Python package contains the supporting tools for converting models from training libraries. Core ML is an Apple framework to integrate machine learning models into your app. Core ML provides a unified representation for all models. Your app uses Core ML APIs and user data to make predictions, and to fine-tune models, all on the user’s device. Core ML optimizes on-device...
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  • 20
    PyTorch Geometric

    PyTorch Geometric

    Geometric deep learning extension library for PyTorch

    ... of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations.
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  • 21
    Transformers4Rec

    Transformers4Rec

    Transformers4Rec is a flexible and efficient library

    ... algorithms usually ignore the temporal dynamics and the sequence of interactions when trying to model user behavior. Generally, the next user interaction is related to the sequence of the user's previous choices. In some cases, it might be a repeated purchase or song play. User interests can also suffer from interest drift because preferences can change over time. Those challenges are addressed by the sequential recommendation task.
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  • 22
    SageMaker Hugging Face Inference Toolkit

    SageMaker Hugging Face Inference Toolkit

    Library for serving Transformers models on Amazon SageMaker

    ... Face Inference Toolkit implements various additional environment variables to simplify your deployment experience. The Hugging Face Inference Toolkit allows user to override the default methods of the HuggingFaceHandlerService. SageMaker Hugging Face Inference Toolkit is licensed under the Apache 2.0 License.
    Downloads: 0 This Week
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  • 23
    OpenAdapt

    OpenAdapt

    Open Source Generative Process Automation

    OpenAdapt is the open source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). OpenAdapt learns to automate your desktop and web workflows by observing your demonstrations. Spend less time on repetitive tasks and more on work that truly matters. Boost team productivity in HR operations. Automate candidate sourcing using LinkedIn Recruiter, LinkedIn Talent Solutions, GetProspect, Reply.io, outreach.io, Gmail/Outlook...
    Downloads: 0 This Week
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  • 24
    AutoGroq

    AutoGroq

    Revolutionizes the way users interact with Autogen

    ... of problems, AutoGroq uses the syntax of the users' needs as the basis for constructing the perfect AI team. It's how we wished Autogen worked from the very beginning. With AutoGroq, a fully configured workflow, team of agents, and skillset are just a few clicks and a couple of minutes away, without any programming necessary. Our rapidly growing user base of nearly 8000 developers is a testament to the power and effectiveness of AutoGroq.
    Downloads: 0 This Week
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  • 25
    FEDML Open Source

    FEDML Open Source

    The unified and scalable ML library for large-scale training

    ... interconnected AI infrastructure layers: user-friendly MLOps, a well-managed scheduler, and high-performance ML libraries for running any AI jobs across GPU Clouds. A typical workflow is shown in the figure above. When a developer wants to run a pre-built job in Studio or Job Store, TensorOperaLaunch swiftly pairs AI jobs with the most economical GPU resources, and auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management.
    Downloads: 0 This Week
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