Search Results for "python basic project" - Page 2
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Showing 251 open source projects for "python basic project"
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Stable Diffusion WebUI
Web interface for generating images using Stable Diffusion models
This project provides a powerful web-based interface for running Stable Diffusion, a text-to-image generation model. Developed by AUTOMATIC1111, it supports numerous features like model customization, prompt history, image upscaling, inpainting, and batch processing. The WebUI is beginner-friendly yet powerful enough for advanced users, becoming one of the most popular community-run UIs for AI image generation. -
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MLRun
Machine Learning automation and tracking
... improvements. In MLRun the assets, metadata, and services (data, functions, jobs, artifacts, models, secrets, etc.) are organized into projects. Projects can be imported/exported as a whole, mapped to git repositories or IDE projects (in PyCharm, VSCode, etc.), which enables versioning, collaboration, and CI/CD. Project access can be restricted to a set of users and roles. -
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Errbot
Chatbot daemon that connects to your favorite chat services
Errbot is a chatbot, a daemon that connects to your favorite chat service and brings your tools into the conversation. The goal of the project is to make it easy for you to write your own plugins so you can make it do whatever you want, a deployment, retrieving some information online, trigger a tool via an API, troll a co-worker, etc. Errbot is being used in a lot of different contexts, chatops (tools for devops), online gaming chatrooms like EVE, video streaming chatrooms like livecoding.tv... -
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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. -
Build apps or websites quickly on a fully managed platformRun frontend and backend services, batch jobs, host LLMs, and queue processing workloads without the need to manage infrastructure.
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PaddleX
PaddlePaddle End-to-End Development Toolkit
PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set... -
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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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doccano
Open source annotation tool for machine learning practitioners
doccano is an open-source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence-to-sequence tasks. So, you can create labeled data for sentiment analysis, named entity recognition, text summarization and so on. Just create a project, upload data and start annotating. You can build a dataset in hours. -
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Dream Textures
Stable Diffusion built-in to Blender
Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what... -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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OpenAssistant
Chat-based assistant that understands tasks
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so. In the same way that Stable Diffusion helped the world make art and images in new ways, we want to improve the world by providing amazing conversational AI. We are in the early stages of development, working from established research in applying RLHF to large language models. Open Assistant is a project organized by LAION and individuals around... -
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ChatDev
Create Customized Software using Natural Language Idea
ChatDev is an AI-powered development tool designed to simulate the software development lifecycle using multi-agent collaboration. It allows multiple AI agents to take on roles such as product managers, developers, and testers to collaboratively generate, refine, and evaluate software code. This project explores how AI can be leveraged to automate and optimize development workflows. -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
MiniSom is a minimalistic and Numpy-based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial Neural Network able to convert complex, nonlinear statistical relationships between high-dimensional data items into simple geometric relationships on a low-dimensional display. Minisom is designed to allow researchers to easily build on top of it and to give students the ability to quickly grasp its details. The project initially aimed for a minimalistic implementation... -
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MONAI
AI Toolkit for Healthcare Imaging
The MONAI framework is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm. Project MONAI also includes MONAI Label, an intelligent open source image labeling and learning tool that helps researchers and clinicians collaborate, create... -
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NVIDIA FLARE
NVIDIA Federated Learning Application Runtime Environment
NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. NVIDIA FLARE is built on a componentized architecture that allows you to take federated... -
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website-to-gif
Turn your website into a GIF
This Github Action automatically creates an animated GIF or WebP from a given web page to display on your project README (or anywhere else). In your GitHub repo, create a workflow file or extend an existing one. You have to also include a step to checkout and commit to the repo. You can use the following example gif.yml. Make sure to modify the url value and add any other input you want to use. WebP rendering will take a lot of time to benefit from lossless quality and file size optimization. -
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Mlxtend
A library of extension and helper modules for Python's data analysis
Mlxtend (machine learning extensions) is a Python library of useful tools for day-to-day data science tasks. -
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Nerfstudio
A collaboration friendly studio for NeRFs
... as an opensource project by Berkeley students in KAIR lab at Berkeley AI Research (BAIR) in October 2022 as a part of a research project (paper). It is currently developed by Berkeley students and community contributors. We are committed to providing learning resources to help you understand the basics of (if you’re just getting started), and keep up-to-date with (if you’re a seasoned veteran) all things NeRF. -
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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 state... -
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SDGym
Benchmarking synthetic data generation methods
... the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device. -
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TextGen
textgen, Text Generation models
Implementation of Text Generation models. textgen implements a variety of text generation models, including UDA, GPT2, Seq2Seq, BART, T5, SongNet and other models, out of the box. UDA, non-core word replacement. EDA, simple data augmentation technique: similar words, synonym replacement, random word insertion, deletion, replacement. This project refers to Google's UDA (non-core word replacement) algorithm and EDA algorithm, based on TF-IDF to replace some unimportant words in sentences... -
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Hivemind
Decentralized deep learning in PyTorch. Built to train models
... averaging: iteratively aggregate updates from multiple workers without the need to synchronize across the entire network. Train neural networks of arbitrary size: parts of their layers are distributed across the participants with the Decentralized Mixture-of-Experts. If you have succesfully trained a model or created a downstream repository with the help of our library, feel free to submit a pull request that adds your project to the list. -
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OpenLIT
OpenLIT is an open-source LLM Observability tool
... your applications are monitored seamlessly, providing critical insights including GPU performance stats for self-hosted LLMs to improve performance and reliability. This project proudly follows the Semantic Conventions of the OpenTelemetry community, consistently updating to align with the latest standards in observability. -
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OpenaiBot
Refractoring ChatBot+LLM, Gpt-3.5-turbo, ChatGPT Bot/Voice Assistant
If you don't have the instant messaging platform you need or you want to develop a new application, you are welcome to contribute to this repository. You can develop a new Controller by using Event.py. Compatibility with multiple LLMs and integration with GPT and third-party systems is handled by our llm-kira project on GitHub. It can accurately limit billing, with limits and ID binding. Supports asynchronous operations and can handle multiple requests simultaneously. Allows for private... -
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Lightly
A python library for self-supervised learning on images
... through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. Experiment with different backbones, models, and loss functions. -
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MetaGPT
The Multi-Agent Framework
The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo. Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated...
