Search Results for "open source" - Page 64
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Showing 16662 open source projects for "open source"
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Alibi Explain
Algorithms for explaining machine learning models
Alibi is a Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-quality implementations of black-box, white-box, local and global explanation methods for classification and regression models. -
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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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WriteTeX
An Inkscape extension: Latex/Tex editor for Inkscape
Due to an incompatible change of the Inkscape extension API, this extension has to split into two versions. For Inkscape versions lower than 1.0, users should use the files in the 0.9.x folder, the other users should use files in the 1.0.x folder. -
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wikmd
A file based wiki that uses markdown
It’s a file-based wiki that aims to simplicity. Instead of storing the data in a database I chose to have a file-based system. The advantage of this system is that every file is directly readable inside a terminal etc. Also when you have direct access to the system you can export the files to anything you like. -
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nbmake
Pytest plugin for testing notebooks
Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks. -
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granary
The social web translator
The social web translator. Fetches and converts data between social networks, HTML and JSON with microformats2, ActivityStreams/ActivityPub, Atom, JSON Feed, and more. Granary is a library and REST API that fetches and converts between a wide variety of social data sources and formats. Free yourself from silo API chaff and expose the sweet social data foodstuff inside in standard formats and protocols. -
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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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py-multiaddr
multiaddr implementation in Python
py-multiaddr is a multiaddr implementation in Python. Every choice in computing has a tradeoff. This includes formats, algorithms, encodings, and so on. And even with a great deal of planning, decisions may lead to breaking changes down the road, or to solutions that are no longer optimal. Allowing systems to evolve and grow is important. The Multiformats Project is a collection of protocols that aim to future-proof systems, today. They do this mainly by enhancing format values with... -
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Woke
Woke is a Python-based development and testing framework for Solidity
Woke is a Python-based development and testing framework for Solidity. A testing framework for Solidity smart contracts with Python-native equivalents of Solidity types and blazing-fast execution. A property-based fuzzer for Solidity smart contracts that allows testers to write their fuzz tests in Python. See examples and documentation for more information. Fuzzer builds on top of the testing framework and allows efficient fuzz testing of Solidity smart contracts. Woke implements an LSP... -
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Selectolax
Python binding to Modest and Lexbor engines
A fast HTML5 parser with CSS selectors using Modest and Lexbor engines. Selectolax supports two backends: Modest and Lexbor. By default, all examples use the Modest backend. Most of the features between backends are almost identical, but there are still some differences. Currently, the Lexbor backend is in beta and missing some of the features. To use lexbor, just import the parser and use it in the similar way to the HTMLParser. -
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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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python-gitlab
A python wrapper for the GitLab API
python-gitlab is a Python package providing access to the GitLab server API. It supports the v4 API of GitLab and provides a CLI tool (GitLab). As of 3.0.0, python-gitlab is compatible with Python 3.7+. -
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Harbor LLM
Run a full local LLM stack with one command using Docker
Harbor is an open source, containerized toolkit designed to simplify running local large language model (LLM) environments. It combines a CLI and companion app to launch backends, frontends, and supporting services with minimal setup. With a single command, users can start preconfigured tools like Ollama and Open WebUI, enabling chat, workflows, and integrations immediately. -
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mergekit
Tools for merging pretrained large language models
mergekit is an open-source toolkit designed to combine multiple pretrained language models into a single unified model through parameter merging techniques. The framework enables developers to merge model checkpoints so that the resulting model inherits capabilities from several source models without requiring additional training. This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of merging algorithms and strategies that control how model parameters are blended together during the merging process. ... -
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USO
Open-sourced unified customization model
USO is ByteDance’s “Unified Style and Subject-Driven Generation” framework, open-sourced to allow customization in generative modeling by disentangling style and subject representation and using reward learning to guide generation. The system is designed such that users can control both “what” is generated (the subject: e.g. a person, object, scene) and “how” it is generated (the style: artistic style, color palette, aesthetic) separately, giving much more flexibility than conventional... -
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SDGym
Benchmarking synthetic data generation methods
The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the... -
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MindsDB
Making Enterprise Data Intelligent and Responsive for AI
MindsDB is an AI data solution that enables humans, AI, agents, and applications to query data in natural language and SQL, and get highly accurate answers across disparate data sources and types. MindsDB connects to diverse data sources and applications, and unifies petabyte-scale structured and unstructured data. Powered by an industry-first cognitive engine that can operate anywhere (on-prem, VPC, serverless), it empowers both humans and AI with highly informed decision-making... -
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dj-stripe
dj-stripe automatically syncs your Stripe Data to your local database
Dj-stripe is an extensible wrapper around the Stripe API that continuously syncs most of the Stripe Data to your local database as pre-implemented Django Models, out of the box! This allows you to use the Django ORM, in your code, to work with the data making it easier and faster! For example, if you need to interact with a customer subscription, you can use dj-stripe’s Subscription Model, in your code, to get the subscription data for that customer as well as the related models’ data too... -
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AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware... -
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TaskingAI
Open platform for building, deploying, and managing LLM agents
TaskingAI is an open source platform designed to simplify the development and deployment of applications powered by large language models. It follows a Backend as a Service approach, allowing developers to separate AI logic from frontend product development while maintaining a structured and scalable workflow. TaskingAI integrates hundreds of language models from multiple providers into a unified system, enabling developers to switch models or combine capabilities without major reconfiguration. ... -
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Semantra
Multi-tool for semantic search
Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. ... -
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owllook
Vertical novel search engine with unified reading and tracking tools
Owllook is an open source vertical search engine designed for discovering and reading online novels from multiple sources. Instead of redirecting users to different sites, the system parses content from many novel platforms and presents it in a unified reading interface. It focuses on providing a simple and comfortable reading experience with features such as searching for books, following updates, bookmarking chapters, and maintaining a personal bookshelf. -
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SeaGOAT
local-first semantic code search engine
SeaGOAT is an open-source semantic code search engine designed to help developers explore and understand large codebases more efficiently. Instead of relying solely on traditional keyword search, it uses vector embeddings to represent the meaning of code and queries, allowing users to perform semantic searches that find relevant code even when the exact keywords are not present. -
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NBA Sports Betting Machine Learning
NBA sports betting using machine learning
NBA-Machine-Learning-Sports-Betting is an open-source Python project that applies machine learning techniques to predict outcomes of National Basketball Association games for analytical and betting-related research. The system gathers historical team statistics and game data spanning multiple seasons, beginning with the 2007–2008 NBA season and continuing through the present. -
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Robyn
Experimental, AI/ML-powered and open sourced Marketing Mix Modeling
Robyn is an open-source, AI/ML-powered Marketing Mix Modeling (MMM) toolkit developed by Meta Marketing Science under the “facebookexperimental” GitHub umbrella. Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of techniques, regularized regression (Ridge), time-series decomposition (trend, seasonality, holiday effects), and hyperparameter optimization (via evolutionary algorithms), to estimate the incremental impact of each marketing channel. ...
