Showing 2627 open source projects for "teams-for-linux"

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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

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  • 1
    NNCF

    NNCF

    Neural Network Compression Framework for enhanced OpenVINO

    NNCF (Neural Network Compression Framework) is an optimization toolkit for deep learning models, designed to apply quantization, pruning, and other techniques to improve inference efficiency.
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  • 2
    API-for-Open-LLM

    API-for-Open-LLM

    Openai style api for open large language models

    API-for-Open-LLM is a lightweight API server designed for deploying and serving open large language models (LLMs), offering a simple way to integrate LLMs into applications.
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  • 3
    DeepSparse

    DeepSparse

    Sparsity-aware deep learning inference runtime for CPUs

    A sparsity-aware enterprise inferencing system for AI models on CPUs. Maximize your CPU infrastructure with DeepSparse to run performant computer vision (CV), natural language processing (NLP), and large language models (LLMs).
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  • 4
    Text Generation Inference

    Text Generation Inference

    Large Language Model Text Generation Inference

    Text Generation Inference is a high-performance inference server for text generation models, optimized for Hugging Face's Transformers. It is designed to serve large language models efficiently with optimizations for performance and scalability.
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  • 5
    openTSNE

    openTSNE

    Extensible, parallel implementations of t-SNE

    openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction algorithm for visualizing high-dimensional data sets. openTSNE incorporates the latest improvements to the t-SNE algorithm, including the ability to add new data points to existing embeddings [2], massive speed improvements [3] [4] [5], enabling t-SNE to scale to millions of data points, and various tricks to improve the global alignment of the resulting...
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  • 6
    Advanced Solutions Lab

    Advanced Solutions Lab

    This repos contains notebooks for the Advanced Solutions Lab

    This repository contains Jupyter notebooks meant to be run on Vertex AI. This is maintained by Google Cloud’s Advanced Solutions Lab (ASL) team. Vertex AI is the next-generation AI Platform on the Google Cloud Platform. The material covered in this repo will take a software engineer with no exposure to machine learning to an advanced level.
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  • 7
    fugue

    fugue

    A unified interface for distributed computing

    Fugue is a unified interface for distributed computing that lets users execute Python, Pandas, and SQL code on Spark, Dask, and Ray with minimal rewrites.
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  • 8
    KerasTuner

    KerasTuner

    A Hyperparameter Tuning Library for Keras

    KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search...
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  • 9
    TensorFlow Datasets

    TensorFlow Datasets

    TFDS is a collection of datasets ready to use with TensorFlow,

    TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data. Datasets , enabling easy-to-use and high-performance input pipelines. To get started see the guide and our list of datasets.
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  • Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure Icon
    Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure

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  • 10
    ScrapeGraphAI

    ScrapeGraphAI

    Python scraper based on AI

    Extracting content from websites and local documents using LLM. ScrapeGraphAI is a web scraping python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, Markdown, etc.). Just say which information you want to extract and the library will do it for you.
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  • 11
    Kor

    Kor

    LLM

    This is a half-baked prototype that “helps” you extract structured data from text using LLMs. Specify the schema of what should be extracted and provide some examples. Kor will generate a prompt, send it to the specified LLM and parse out the output. You might even get results back.
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  • 12
    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...
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  • 13
    Megatron

    Megatron

    Ongoing research training transformer models at scale

    Megatron is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA. This repository is for ongoing research on training large transformer language models at scale. We developed efficient, model-parallel (tensor, sequence, and pipeline), and multi-node pre-training of transformer based models such as GPT, BERT, and T5 using mixed precision. Megatron is also used in NeMo Megatron, a framework to help enterprises overcome the challenges of building and...
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  • 14
    pycm

    pycm

    Multi-class confusion matrix library in Python

    PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters. PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scientists that need a broad array of metrics for predictive models and an accurate evaluation of large variety of classifiers.
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  • 15
    h2oGPT

    h2oGPT

    Private chat with local GPT with document, images, video, etc.

    h2oGPT is an open-source platform that allows users to interact with local GPT models in a completely private environment. It supports a variety of document types, including PDFs, Word files, images, video frames, and even audio, enabling users to query and analyze their documents or engage in a private chat with AI. The platform is designed to be secure and offline, ensuring that all data remains private and under the user's control. h2oGPT supports several AI models, including oLLaMa and...
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  • 16
    tf2onnx

    tf2onnx

    Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX

    tf2onnx converts TensorFlow (tf-1.x or tf-2.x), keras, tensorflow.js and tflite models to ONNX via command line or python API. Note: tensorflow.js support was just added. While we tested it with many tfjs models from tfhub, it should be considered experimental. TensorFlow has many more ops than ONNX and occasionally mapping a model to ONNX creates issues. tf2onnx will use the ONNX version installed on your system and installs the latest ONNX version if none is found. We support and test ONNX...
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  • 17
    NErlNet

    NErlNet

    Nerlnet is a framework for research and development

    NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices.
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  • 18
    Llama Cookbook

    Llama Cookbook

    Solve end to end problems using Llama model family

    The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models
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  • 19
    Upsonic

    Upsonic

    The most reliable AI agent framework that supports MCP

    Upsonic is a reliability-focused AI agent framework designed for real-world applications. It enables the development of trusted agent workflows within organizations by incorporating advanced reliability features, such as verification layers and output evaluation systems. The framework supports the Model Context Protocol (MCP), facilitating integration with various tools and enhancing agent capabilities. ​
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  • 20
    MCP Server Qdrant

    MCP Server Qdrant

    An official Qdrant Model Context Protocol (MCP) server implementation

    The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. ​
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  • 21
    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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  • 22
    Clay Foundation Model

    Clay Foundation Model

    The Clay Foundation Model - An open source AI model and interface

    The Clay Foundation Model is an open-source AI model and interface designed to provide comprehensive data and insights about Earth. It aims to serve as a foundational tool for environmental monitoring, research, and decision-making by integrating various data sources and offering an accessible platform for analysis.
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  • 23
    Dev-template

    Dev-template

    A template for development with the open-autonomy framework

    Dev Template is a starting point for developing autonomous agents using the Autonolas framework by Valory. It provides a modular and extensible codebase to accelerate the development of agents that act autonomously in decentralized networks. This template includes tooling for building, testing, and deploying agents in real-world decentralized applications (dApps).
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  • 24
    RL Baselines3 Zoo

    RL Baselines3 Zoo

    Training framework for Stable Baselines3 reinforcement learning agents

    rl-baselines3-zoo is a collection of pre-trained models, benchmarks, and hyperparameter tuning tools built on top of Stable Baselines3, a reinforcement learning library. It provides an easy way to test, evaluate, and train RL agents across a wide variety of environments.
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  • 25
    Mctx

    Mctx

    Monte Carlo tree search in JAX

    mctx is a Monte Carlo Tree Search (MCTS) library developed by Google DeepMind for reinforcement learning research. It enables efficient and flexible implementation of MCTS algorithms, including those used in AlphaZero and MuZero.
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