Search Results for "python programming language" - Page 26

Showing 2811 open source projects for "python programming language"

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  • 1
    CRAB

    CRAB

    CRAB: Cross-environment Agent Benchmark for Multimodal Language Model

    CRAB (Composable and Reusable Autonomous Bots) is a framework for building modular, reusable AI agents that can perform complex tasks in various domains. It focuses on creating AI-driven workflows that can be composed of multiple autonomous agents working together.
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  • 2
    TapeAgents

    TapeAgents

    A framework that facilitates all stages of LLM development

    TapeAgents is a framework that facilitates all stages of the Large Language Model (LLM) agent development lifecycle, providing tools for building, testing, and deploying AI agents.
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  • 3
    Parlant

    Parlant

    The behavior guidance framework for customer-facing LLM agents

    Parlant is a lightweight speech-to-text and text-to-speech framework designed for real-time AI-driven voice applications.
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  • 4
    Backtrack Sampler

    Backtrack Sampler

    An easy-to-understand framework for LLM samplers

    Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs.
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  • 5
    Textinator

    Textinator

    Internationalized highly customizable annotation and evaluation tool

    Textinator is an open-source internationalized highly-customizable annotation and evaluation tool for Natural Language Processing (NLP) tasks. The tool offers a web interface with a user-friendly UI and supports a number of NLP tasks out of the box. The recommended way of deploying Textinator is through building a production version of the Docker container, as described in the Deployment guidelines. Note that the production version is most definitely more secure and reliable than...
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  • 6
    AudioLM - Pytorch

    AudioLM - Pytorch

    Implementation of AudioLM audio generation model in Pytorch

    Implementation of AudioLM, a Language Modeling Approach to Audio Generation out of Google Research, in Pytorch It also extends the work for conditioning with classifier free guidance with T5. This allows for one to do text-to-audio or TTS, not offered in the paper. Yes, this means VALL-E can be trained from this repository. It is essentially the same. This repository now also contains a MIT licensed version of SoundStream. It is also compatible with EnCodec, however, be aware that it has...
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  • 7
    BitNet

    BitNet

    Inference framework for 1-bit LLMs

    BitNet (bitnet.cpp) is a high-performance inference framework designed to optimize the execution of 1-bit large language models, making them more efficient for edge devices and local deployment. The framework offers significant speedups and energy reductions, achieving up to 6.17x faster performance on x86 CPUs and 70% energy savings, allowing the running of models such as the BitNet b1.58 100B with impressive efficiency. With support for lossless inference and enhanced processing power, BitNet...
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  • 8
    Infinity

    Infinity

    Low-latency REST API for serving text-embeddings

    Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. Infinity is developed under MIT License. Infinity powers inference behind Gradient.ai and other Embedding API providers.
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  • 9
    Aviary

    Aviary

    Ray Aviary - evaluate multiple LLMs easily

    Aviary is an LLM serving solution that makes it easy to deploy and manage a variety of open source LLMs. Providing an extensive suite of pre-configured open source LLMs, with defaults that work out of the box. Supporting Transformer models hosted on Hugging Face Hub or present on local disk. Aviary has native support for autoscaling and multi-node deployments thanks to Ray and Ray Serve. Aviary can scale to zero and create new model replicas (each composed of multiple GPU workers) in...
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  • 10
    OpenDAN

    OpenDAN

    OpenDAN is an open source Personal AI OS

    OpenDAN is an open-source Personal AI OS , that consolidates various AI modules in one place for your personal use. The goal of OpenDAN (Open and Do Anything Now with AI) is to create a Personal AI OS , which provides a runtime environment for various Al modules as well as protocols for interoperability between them. With OpenDAN, users can securely collaborate with various AI modules using their private data to create powerful personal AI agents, such as butlers, lawyers, doctors, teachers,...
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  • 11
    Chinese-LLaMA-Alpaca 2

    Chinese-LLaMA-Alpaca 2

    Chinese LLaMA-2 & Alpaca-2 Large Model Phase II Project

    This project is developed based on the commercially available large model Llama-2 released by Meta. It is the second phase of the Chinese LLaMA&Alpaca large model project. The Chinese LLaMA-2 base model and the Alpaca-2 instruction fine-tuning large model are open-sourced. These models expand and optimize the Chinese vocabulary on the basis of the original Llama-2, use large-scale Chinese data for incremental pre-training, and further improve the basic semantics and command understanding of...
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  • 12
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    ... learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. Jittor'op is similar to NumPy. Let's try some operations. We create Var a and b via operation jt.float32, and add them. Printing those variables shows they have the same shape and dtype.
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  • 13
    SHAP

    SHAP

    A game theoretic approach to explain the output of ml models

    SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods. Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark...
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  • 14
    Go support for Protocol Buffers

    Go support for Protocol Buffers

    The Go support for Google's protocol buffers

    Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data, think XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. Protocol buffers currently support generated code in Java, Python, Objective-C, and C++. With our new proto3...
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  • 15
    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.
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  • 16
    Sloc Cloc and Code (scc)

    Sloc Cloc and Code (scc)

    Sloc, Cloc and Code: scc is a very fast accurate code counter

    Sloc, Cloc and Code: scc is a very fast accurate code counter with complexity calculations and COCOMO estimates written in pure Go. The tool is similar to cloc, sloccount and tokei. For counting the lines of code, blank lines, comment lines, and physical lines of source code in many programming languages. The goal is to be the fastest code counter possible, but also perform COCOMO calculations like sloccount, estimate code complexity similar to cyclomatic complexity calculators, and produce...
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  • 17
    Feishu ChatGPT

    Feishu ChatGPT

    Voice dialogue, role-playing, multi-topic discussion, picture creation

    Feishu × (GPT-3.5 + DALL·E + Whisper) = flying-like work experience. Voice dialogue, role-playing, multi-topic discussion, picture creation, table analysis, document export. Golang language, it goes without saying! Master the gin framework proficiently, developing the backend is as natural as breathing! Familiar with the SDKs of DingTalk, Feishu, Qiwei and other platforms, and be able to develop and integrate a series of amazing functions! Proficient in platform-based detail thinking, let...
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  • 18
    Hakaton Starter

    Hakaton Starter

    A boilerplate for Node.js web applications

    A boilerplate for Node.js web applications. If you have attended any hackathons in the past, then you know how much time it takes to get a project started: decide on what to build, pick a programming language, pick a web framework, pick a CSS framework. A while later, you might have an initial project up on GitHub, and only then can other team members start contributing. Or how about doing something as simple as Sign in with Facebook authentication? You can spend hours on it if you...
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  • 19
    YamlDotNet

    YamlDotNet

    YamlDotNet is a .NET library for YAML

    YamlDotNet provides low-level parsing and emitting of YAML as well as a high-level object model similar to XmlDocument. A serialization library is also included that allows to read and write objects from and to YAML streams. YAML, which stands for "YAML Ain't Markup Language", is described as "a human-friendly data serialization standard for all programming languages". Like XML, it allows to represent of any kind of data in a portable, platform-independent format. Unlike XML, it is "human...
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  • 20
    AWS Secrets Manager Go Caching Client

    AWS Secrets Manager Go Caching Client

    Enables in-process caching of secrets for Go applications

    The AWS Secrets Manager Go caching client enables in-process caching of secrets for Go applications. To use this client you must have a Go development environment. If you do not have one, go to Golang Getting Started on The Go Programming Language website, then download and install Go. An Amazon Web Services (AWS) account to access secrets stored in AWS Secrets Manager and use AWS SDK for Go. To create an AWS account, go to Sign In or Create an AWS Account and then choose I am a new user...
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  • 21
    AWS X-Ray SDK for Go

    AWS X-Ray SDK for Go

    AWS X-Ray SDK for the Go programming language

    AWS X-Ray recommends using AWS Distro for OpenTelemetry (ADOT) to instrument your application instead of this X-Ray SDK due to its wider range of features and instrumentations. See the AWS X-Ray docs on Working with Go for more help with choosing between ADOT and X-Ray SDK. Install the SDK using the following command (The SDK's non-testing dependencies will be installed): Use go get to retrieve the SDK to add it to your GOPATH workspace. X-Ray Go SDK will by default generate no-op trace and...
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  • 22
    AWS CodeBuild curated Docker images

    AWS CodeBuild curated Docker images

    AWS CodeBuild repository for managed Docker images

    When you call AWS CodeBuild to run a build, you must provide information about the build environment. A build environment represents a combination of operating system, programming language runtime, and tools that CodeBuild uses to run a build. The master branch will sometimes have changes that are still in the process of being released in AWS CodeBuild. When you provide information to CodeBuild about the build environment, you specify the identifier of a Docker image in a supported repository...
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  • 23
    Swagger 2.0

    Swagger 2.0

    Swagger 2.0 implementation for go

    This package contains a golang implementation of Swagger 2.0 (aka OpenAPI 2.0), it knows how to serialize and deserialize swagger specifications. With the largest ecosystem of API tooling on the planet, thousands of developers are supporting Swagger in almost every modern programming language and deployment environment. With a Swagger-enabled API, you get interactive documentation, client SDK generation and discoverability. We created Swagger to help fulfill the promise of APIs. Swagger helps...
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  • 24
    Ebiten

    Ebiten

    A dead simple 2D game library for Go

    Ebiten is an open source game library for the Go programming language. Ebiten's simple API allows you to quickly and easily develop 2D games that can be deployed across multiple platforms. In Ebiten, everything is an image: the screen, data from an image file, and even offscreen items are all represented as image objects. Most rendering operations consist of drawing one image on top of another. Ebiten games work on desktop (Windows, macOS, Linux, and FreeBSD), web browsers (through WebAssembly...
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  • 25
    DifferentialEquations.jl

    DifferentialEquations.jl

    Multi-language suite for high-performance solvers of equations

    This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research which routinely outperform the “standard” C/Fortran methods, and include algorithms optimized...
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