Search Results for "code" - Page 29
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Showing 2491 open source projects for "code"
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imodelsX
Interpretable prompting and models for NLP
Interpretable prompting and models for NLP (using large language models). Generates a prompt that explains patterns in data (Official) Explain the difference between two distributions. Find a natural-language prompt using input-gradients. Fit a better linear model using an LLM to extract embeddings. Fit better decision trees using an LLM to expand features. Finetune a single linear layer on top of LLM embeddings. Use these just a like a sci-kit-learn model. During training, they fit better... -
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Sanic
Async Python 3.6+ web server/framework
...Sanic aspires to be as simple as possible while delivering the performance that you require. It allows the usage of the async/await syntax added in Python 3.5, so your code is guaranteed to be non-blocking and speedy. It's also ASGI compliant, so it's possible to deploy with an alternative ASGI webserver. -
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mergekit
Tools for merging pretrained large language models
...The library is designed to operate efficiently even in environments with limited hardware resources by using memory-efficient processing methods that can run entirely on CPUs. It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code. -
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AWS SDK for pandas
Easy integration with Athena, Glue, Redshift, Timestream, Neptune
aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. ... -
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cheat.sh
The only cheat sheet you need
...You can query it from the terminal (for example curl cht.sh/rsync or curl cheat.sh/ls) or browse the web front page; it also supports a shorthand hostname (cht.sh) and provides both online and standalone/local installation modes. The repository contains the server and client code, instructions to run a local standalone instance (including Python virtualenv setup), and tooling to fetch or maintain the upstream cheat-sheet data; installation documentation explains disk-space needs and dependency setup for offline use. Cheat.sh is intentionally minimal and scriptable, so it fits naturally into shells, CI scripts, editors, and quick lookups without leaving the terminal, while also offering ways to extend or host personal cheat sheets. -
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OctoBot
Cryptocurrency trading bot for TA, arbitrage and social trading
OctoBot is a trading robot that is designed to be easy to use and infinitely customizable. OctoBot is built for people who don't have much time or do not easily trust crypto-world projects. Many trading automation tools exist but most of them are complicated to use, expensive, do not behave as intended, or are meant to be used by professional traders. Moreover, when a favorable trend is spotted, it can be difficult to maximize profit from it: trading takes a lot of time, and when it's done... -
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OWL
Optimized Workforce Learning for General Multi-Agent Assistance
OWL (Optimized Workforce Learning) is a sophisticated open-source framework built on the CAMEL-AI ecosystem for orchestrating teams of AI agents to collaboratively solve complex, real-world tasks with dynamic planning and automation capabilities. Unlike single-agent systems, it treats task completion as a collaborative workforce where agents take on specialized roles (planning, execution, analysis) and coordinate via a modular multi-agent architecture that supports flexible teamwork across... -
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Shiptest
The Shiptest Codebase
...Instead of being confined to one station, players can design, operate, and explore with their own ships in a shared space environment. The repository contains full source code, assets, and maps to host or develop servers. Shiptest introduces new mechanics around ship construction, navigation, and resource management, creating a sandbox that emphasizes exploration and collaboration. Its modular design allows for diverse playstyles, from engineering and trade to combat and survival. The project is actively updated by its community, pushing SS13 gameplay in a fresh, experimental direction. -
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...The repository contains the full SS13 codebase with modifications, including custom jobs, items, maps, and quality-of-life improvements. Yogstation prioritizes accessibility for new players while maintaining depth for veterans, making it one of the more popular SS13 community forks. The code and assets are open for contribution, allowing developers to propose fixes, features, and balance changes. With active updates, Yogstation continues to evolve as a distinctive branch of the SS13 ecosystem.
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nbdev
Create delightful software with Jupyter Notebooks
nbdev is a notebook-driven development platform (by fast.ai/AnswerDotAI) enabling you to write code, tests, documentation, and deploy software, all from Jupyter Notebooks. It provides a unified literate programming workflow where you can tag notebook cells for export to Python modules, auto-generate documentation via Quarto (and host it on GitHub Pages), run tests embedded in notebooks, manage clean notebooks with Git-friendly metadata hooks, and seamlessly publish packages to PyPI/conda, all while keeping source and documentation in sync. -
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LatentSync
Taming Stable Diffusion for Lip Sync
LatentSync is an open-source framework from ByteDance that produces high-quality lip-synchronization for video by using an audio-conditioned latent diffusion model, bypassing traditional intermediate motion representations. In effect, given a source video (with masked or reference frames) and an audio track, LatentSync directly generates frames whose lip motions and expressions align with the audio, producing convincing talking-head or animated lip-sync output. The system leverages a U-Net... -
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CleanVision
Automatically find issues in image datasets
...This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset! The quality of machine learning models hinges on the quality of the data used to train them, but it is hard to manually identify all of the low-quality data in a big dataset. CleanVision helps you automatically identify common types of data issues lurking in image datasets. This package currently detects issues in the raw images themselves, making it a useful tool for any computer vision task such as: classification, segmentation, object detection, pose estimation, keypoint detection, generative modeling, etc. -
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Liberapay
Source code of the recurrent donations platform Liberapay
Liberapay is an open-source platform designed to facilitate recurring donations to creators, developers, and projects, with a strong emphasis on transparency, privacy, and sustainability. It operates as a nonprofit service that allows users to financially support individuals or teams on a weekly, monthly, or yearly basis without expecting rewards in return. The platform is particularly focused on funding open-source software, free knowledge, and creative work, helping contributors maintain... -
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SCAIL
Towards Studio-Grade Character Animation via In-Context Learning of 3D
SCAIL is a project developed by the ZAI Organization, focusing on AI-driven research initiatives. While specific documentation about SCAIL’s exact goals and implementation is limited from the repository context alone, the project appears to be part of a collection of machine learning and AI research tools that facilitate scalable model development, evaluation, or application workflows. Given its listing alongside other ZAI projects like speech recognition and text-to-speech systems, SCAIL... -
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Flask-Migrate
SQLAlchemy database migrations for Flask applications using Alembic
...It provides a set of command-line routines tied into Flask’s CLI such that developers can generate migration scripts, apply upgrades, and roll back changes with simple commands, keeping the database structure in sync with evolving application models. The extension handles versioning of the database schema so teams can track and share structural changes alongside application code, reducing manual migration errors and enabling collaborative development. Flask-Migrate also supports branching and merging workflows by generating human-readable migration scripts that developers can review, edit, and commit to version control. -
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Gemma in PyTorch
The official PyTorch implementation of Google's Gemma models
...The repository demonstrates text generation pipelines, tokenizer setup, quantization paths, and adapters for low-rank or parameter-efficient fine-tuning. Example notebooks walk through instruction tuning and evaluation so teams can benchmark and iterate rapidly. The code is organized to be legible and hackable, exposing attention blocks, positional encodings, and head configurations. With standard PyTorch abstractions, it integrates easily into existing training loops, loggers, and evaluation harnesses. -
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Web Dev for Beginners
About 24 Lessons, 12 Weeks, Get Started as a Web Developer
...The course also offers global accessibility with translations in more than 40 languages and built-in support for running in GitHub Codespaces or locally in Visual Studio Code. This makes it a practical and engaging way for beginners to gain a solid foundation in web development. -
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TorchDistill
A coding-free framework built on PyTorch
torchdistill (formerly kdkit) offers various state-of-the-art knowledge distillation methods and enables you to design (new) experiments simply by editing a declarative yaml config file instead of Python code. Even when you need to extract intermediate representations in teacher/student models, you will NOT need to reimplement the models, which often change the interface of the forward, but instead specify the module path(s) in the yaml file. In addition to knowledge distillation, this framework helps you design and perform general deep learning experiments (WITHOUT coding) for reproducible deep learning studies. i.e., it enables you to train models without teachers simply by excluding teacher entries from a declarative yaml config file. -
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Jupytext
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
Have you always wished Jupyter notebooks were plain text documents? Wished you could edit them in your favorite IDE? And get clear and meaningful diffs when doing version control? Then, Jupytext may well be the tool you’re looking for. Only the notebook inputs (and optionally, the metadata) are included. Text notebooks are well suited for version control. You can also edit or refactor them in an IDE - the .py notebook above is a regular Python file. Text notebooks with a .py or .md extension... -
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django-money
Money fields for Django forms and models
A little Django app that uses py-moneyed to add support for Money fields in your models and forms. The default currency code length is 3 but you can change it with the CURRENCY_CODE_MAX_LENGTH setting. Currencies are listed on moneyed, and these modules use this to provide a choice list on the admin, also for validation. Django-money leaves you to use any custom model managers you like for your models, but it needs to wrap some of the methods to allow searching for models with money values. ... -
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Faker for Python
Python package that generates fake data for you
Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you. Starting from version 4.0.0, Faker dropped support for Python 2 and from version 5.0.0 only supports Python 3.6 and above. If you still need Python 2 compatibility, please install version 3.0.1 in the meantime, and please consider updating... -
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AndroidNativeEmu
Allows you to partly emulate an Android native library
AndroidNativeEmu is a Python-based framework designed to partially emulate Android native libraries, enabling developers and researchers to analyze and execute native code outside of a full Android environment. Instead of emulating an entire operating system, it focuses specifically on the native layer, allowing for targeted testing and reverse engineering of shared libraries (.so files). This makes it particularly useful in security research, malware analysis, and debugging of Android applications. ... -
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ARIS
Lightweight Markdown-only skills for autonomous ML research
...The system is designed to run iterative cycles of research, coding, testing, and refinement, effectively simulating a “sleep mode” where productive work continues in the background. It integrates with AI tools such as Claude Code to generate solutions, analyze results, and improve outputs over time. The project emphasizes long-running workflows that can explore problem spaces more deeply than manual intervention would typically allow. It also highlights the potential of autonomous agents to handle repetitive or exploratory tasks that would otherwise require significant human effort. ... -
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TypeAgent Python
Structured RAG: ingest, index, query
...This design allows the system to combine the flexibility of language models with the reliability of traditional programming logic. The repository is intended primarily as a research prototype and sample code rather than a production-ready framework, allowing developers to experiment with building AI agents that maintain structured memory and perform tasks through defined actions. -
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SimpleHTR
Handwritten Text Recognition (HTR) system implemented with TensorFlow
...It also employs connectionist temporal classification (CTC) to align predicted character sequences with input images without requiring character-level segmentation. The repository provides code for training models, performing inference on handwritten text images, and evaluating recognition accuracy. SimpleHTR is commonly used as an educational example for understanding how modern handwriting recognition systems operate.
