Search Results for "raspberry-gpio-python" - Page 17
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Showing 1810 open source projects for "raspberry-gpio-python"
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Fairlearn
A Python package to assess and improve fairness of ML models
Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. An AI system can behave unfairly for a variety of reasons. In Fairlearn, we define whether an AI system is behaving unfairly in terms... -
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Bard API
The unofficial python package that returns response of Google Bard
The Python package returns a response of Google Bard through the value of the cookie. This package is designed for application to the Python package ExceptNotifier and Co-Coder. Please note that the bardapi is not a free service, but rather a tool provided to assist developers with testing certain functionalities due to the delayed development and release of Google Bard's API. It has been designed with a lightweight structure that can easily adapt to the emergence of an official API. Therefore... -
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Awesome-FL
Comprehensive and timely academic information on federated learning
A “awesome” curated list of federated learning (FL) academic resources: research papers, tools, frameworks, datasets, tutorials, and workshops. A hub for FL knowledge maintained by the academic community. -
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Airweave
Airweave lets agents search any app
Airweave is an open-source platform that enables agents to semantically search across various applications, databases, and APIs. By transforming disparate data sources into a unified, searchable knowledge base, Airweave facilitates intelligent information retrieval through REST APIs or the MCP protocol. It's particularly useful for building AI agents that require access to structured and unstructured data across multiple platforms. -
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MCP Atlassian
MCP server that integrates Confluence and Jira
The MCP Atlassian server integrates Atlassian products like Confluence and Jira with the Model Context Protocol. It supports both Cloud and Server/Data Center deployments, enabling AI models to interact with these platforms securely. -
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MCP ZoomEye
A Model Context Protocol server that provides network asset info
The ZoomEye MCP Server is a Model Context Protocol server that provides network asset information based on query conditions, allowing Large Language Models to obtain data by querying ZoomEye using dorks and other search parameters. -
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MCP Text Editor
Provides line-oriented text file editing capabilities
The MCP Text Editor Server provides line-oriented text file editing capabilities through a standardized API, optimized for integration with Large Language Models (LLMs). It enables efficient partial file access, minimizing token usage while ensuring safe concurrent editing. -
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Airtable MCP
Airtable integration for AI-powered applications
Airtable MCP is an integration tool that enables AI-powered applications to access and manipulate Airtable databases directly from the IDE using Anthropic's Model Context Protocol (MCP). It allows querying, creating, updating, and deleting records using natural language, facilitating seamless data management. -
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Elasticsearch MCP Server
A Model Context Protocol (MCP) server implementation
This MCP server implementation provides interaction capabilities with Elasticsearch and OpenSearch, enabling functionalities such as document searching, index analysis, and cluster management through a set of tools. -
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FlashInfer
FlashInfer: Kernel Library for LLM Serving
FlashInfer is a kernel library designed to enhance the serving of Large Language Models (LLMs) by optimizing inference performance. It provides a high-performance framework that integrates seamlessly with existing systems, aiming to reduce latency and improve efficiency in LLM deployments. FlashInfer supports various hardware architectures and is built to scale with the demands of production environments. -
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optillm
Optimizing inference proxy for LLMs
OptiLLM is an optimizing inference proxy for Large Language Models (LLMs) that implements state-of-the-art techniques to enhance performance and efficiency. It serves as an OpenAI API-compatible proxy, allowing for seamless integration into existing workflows while optimizing inference processes. OptiLLM aims to reduce latency and resource consumption during LLM inference. -
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FastRAG
Efficient Retrieval Augmentation and Generation Framework
fastRAG is a research framework for efficient and optimized retrieval augmented generative pipelines, incorporating state-of-the-art LLMs and Information Retrieval. fastRAG is designed to empower researchers and developers with a comprehensive tool set for advancing retrieval augmented generation. -
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Chonkie
The no-nonsense RAG chunking library
Chonkie is an AI-powered framework designed for building conversational agents and chatbots with natural language understanding and multi-turn conversation support. -
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AdalFlow
The library to build & auto-optimize LLM applications
AdalFlow is a framework for building AI-powered automation workflows, enabling users to design and execute intelligent automation pipelines with minimal coding. -
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Data-Juicer
Data processing for and with foundation models
Data-Juicer is an open-source data processing and augmentation framework designed to enhance the quality and diversity of datasets for machine learning tasks. It includes a modular pipeline for scalable data transformation. -
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TruLens
Evaluation and Tracking for LLM Experiments
TruLens is an open-source Python library designed to systematically evaluate and track Large Language Model (LLM) applications. It provides fine-grained instrumentation, feedback functions, and a user interface to compare and iterate on app versions, facilitating rapid development and improvement of LLM-based applications. Programmatic tools that assess the quality of inputs, outputs, and intermediate results from LLM applications, enabling scalable evaluation. Fine-grained, stack-agnostic... -
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uAgents
A fast and lightweight framework for creating decentralized agents
uAgents is a library developed by Fetch.ai that allows for creating autonomous AI agents in Python. With simple and expressive decorators, you can have an agent that performs various tasks on a schedule or takes action on various events. -
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Agentic Security
Agentic LLM Vulnerability Scanner / AI red teaming kit
The open-source Agentic LLM Vulnerability Scanner. -
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fklearn
Functional Machine Learning
fklearn uses functional programming principles to make it easier to solve real problems with Machine Learning. -
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pomegranate
Fast, flexible and easy to use probabilistic modelling in Python
pomegranate is a library for probabilistic modeling defined by its modular implementation and treatment of all models as the probability distributions they are. The modular implementation allows one to easily drop normal distributions into a mixture model to create a Gaussian mixture model just as easily as dropping a gamma and a Poisson distribution into a mixture model to create a heterogeneous mixture. But that's not all! Because each model is treated as a probability distribution,... -
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Hummingbird
Hummingbird compiles trained ML models into tensor computation
Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to seamlessly leverage neural network frameworks (such as PyTorch) to accelerate traditional ML models. Thanks to Hummingbird, users can benefit from (1) all the current and future optimizations implemented in neural network frameworks; (2) native hardware acceleration; (3) having a unique platform to support both traditional and neural network models; and having all of... -
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supervision
We write your reusable computer vision tools
We write your reusable computer vision tools. Whether you need to load your dataset from your hard drive, draw detections on an image or video, or count how many detections are in a zone. You can count on us. -
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OpenLLM
Operating LLMs in production
..., CLI, our Python/Javascript client, or any HTTP client. -
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img2dataset
Easily turn large sets of image urls to an image dataset
Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine. Also supports saving captions for url+caption datasets. Opt-out directives: Websites can pass the http headers X-Robots-Tag: noai, X-Robots-Tag: noindex , X-Robots-Tag: noimageai and X-Robots-Tag: noimageindex By default img2dataset will ignore images with such headers. -
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EvaDB
Database system for building simpler and faster AI-powered application
Over the last decade, AI models have radically changed the world of natural language processing and computer vision. They are accurate on various tasks ranging from question answering to object tracking in videos. To use an AI model, the user needs to program against multiple low-level libraries, like PyTorch, Hugging Face, Open AI, etc. This tedious process often leads to a complex AI app that glues together these libraries to accomplish the given task. This programming complexity prevents...
