Search Results for "example" - Page 3
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Showing 512 open source projects for "example"
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deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
...It implements the core logic needed to train an agent using Q-learning with neural networks (i.e. approximating Q-values via deep nets), setting up environment interaction loops, experience replay, network updates, and policy behavior. For learners and researchers interested in reinforcement learning, this repo offers a concrete, runnable example bridging theory and practice: you can execute the code, play with hyperparameters, observe convergence behavior, and see how deep Q-learning learns policies over time in standard environments. Because it’s self-contained and Python-based, it's well-suited for experimentation, modifications, or extension — for instance adapting to custom Gym environments, tweaking network architecture, or combining with other RL techniques. -
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Mistral Finetune
Memory-efficient and performant finetuning of Mistral's models
...It builds on techniques like LoRA (Low-Rank Adaptation) to allow customizing models without full parameter updates, which reduces GPU memory footprint and training cost. The repo includes utilities for data preprocessing (e.g. reformat_data.py), validation scripts, and example YAML configs for training variants like 7B base or instruct models. It supports function-calling style datasets (via "messages" keys) as well as plain text formats, with guidelines on formatting, tokenization, and vocabulary extension (e.g. extending vocab to 32768 for some models) before finetuning. The project also provides tutorial notebooks (e.g. mistral_finetune_7b.ipynb) to walk through the steps. -
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System Design Primer
Learn how to design large-scale systems
System Design Primer is a curated, open source collection of resources that helps engineers learn how to design large-scale systems. The project is structured as a comprehensive guide covering core system design concepts, trade-offs, and patterns necessary for building scalable, reliable, and maintainable systems. It offers both theoretical foundations—such as scalability principles, the CAP theorem, and consistency models—and practical exercises, including real-world system design interview... -
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SAM 3D Objects
Models for object and human mesh reconstruction
SAM 3D Objects is a foundation model that reconstructs full 3D geometry, texture, and spatial layout of objects and scenes from a single image. Given one RGB image and object masks (for example, from the Segment Anything family), it can generate a textured 3D mesh for each object, including pose and approximate scene layout. The model is specifically designed to be robust in real-world images with clutter, occlusions, small objects, and unusual viewpoints, where many earlier 3D-from-image systems struggle. It supports both single-object and multi-object generation, allowing you to reconstruct entire scenes rather than just isolated items. ... -
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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PaperQA2
High accuracy RAG for answering questions from scientific documents
...See our recent 2024 paper to see examples of PaperQA2's superhuman performance in scientific tasks like question answering, summarization, and contradiction detection. In this example we take a folder of research paper PDFs, magically get their metadata - including citation counts and a retraction check, then parse and cache PDFs into a full-text search index, and finally answer the user question with an LLM agent. -
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iTerm2 Color Schemes
Over 425 terminal color schemes/themes for iTerm/iTerm2
This project curates a large collection of terminal color schemes and makes them available in formats for many terminal emulators, not just iTerm2. You’ll find well-known palettes like Solarized, Dracula, Nord, and hundreds more, each with previews that showcase how code, prompts, and text look under the theme. The repository includes export files for multiple terminals—such as iTerm2, Apple Terminal, Alacritty, Kitty, Windows Terminal, and others—so you can apply the same aesthetic... -
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Janus
Unified Multimodal Understanding and Generation Models
...By splitting those pathways but keeping one unified core transformer, Janus maintains flexibility and achieves strong performance across tasks previously requiring distinct architectures. The repository includes pretrained checkpoints (for example 1.3B and 7B parameter versions), a Gradio demo, and guidance for local deployment. -
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wxPython Project Phoenix
wxPython's Project Phoenix. A new implementation of wxPython
wxPython, the cross-platform GUI toolkit for the Python language. With wxPython software developers can create truly native user interfaces for their Python applications, that run with little or no modifications on Windows, Macs and Linux or other Unix-like systems. Welcome to wxPython's Project Phoenix! Phoenix is the improved next-generation wxPython, "better, stronger, faster than he was before." This new implementation is focused on improving speed, maintainability and extensibility.... -
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GLM-4
GLM-4 series: Open Multilingual Multimodal Chat LMs
GLM-4 is a family of open models from ZhipuAI that spans base, chat, and reasoning variants at both 32B and 9B scales, with long-context support and practical local-deployment options. The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Search with Lepton
Lightweight demo to build a conversational AI search engine quickly
...It retrieves information from supported search engines and uses that context to generate responses through a retrieval-augmented generation approach. The implementation is intentionally minimal, containing fewer than 500 lines of code while still providing a complete working example of an AI-powered search system. It includes both a backend service written in Python and a web interface that allows users to interact with the search engine in a conversational format. Developers can configure different search providers and language models through environment variables, making it flexible for experimentation and prototyping. -
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Flower
Flower: A Friendly Federated Learning Framework
...Many components can be extended and overridden to build new state-of-the-art systems. Different machine learning frameworks have different strengths. Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand. -
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HyperTools
A Python toolbox for gaining geometric insights
HyperTools is a library for visualizing and manipulating high-dimensional data in Python. It is built on top of matplotlib (for plotting), seaborn (for plot styling), and scikit-learn (for data manipulation). Functions for plotting high-dimensional datasets in 2/3D. Static and animated plots. Simple API for customizing plot styles. Set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more. Support for lists of Numpy arrays, Pandas dataframes,... -
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PyTorch Ignite
Library to help with training and evaluating neural networks
...Use ignite where and when you need. Extensible API for metrics, experiment managers, and other components. The cool thing with handlers is that they offer unparalleled flexibility (compared to, for example, callbacks). Handlers can be any function: e.g. lambda, simple function, class method, etc. Thus, we do not require to inherit from an interface and override its abstract methods which could unnecessarily bulk up your code and its complexity. Extremely simple engine and event system. Out-of-the-box metrics to easily evaluate models. ... -
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Watchman
A file watching service that records when files change
Watchman purpose is to watch files and record when there are changes. It can trigger actions (rebuilding assets, for example) when there is a change in matching files. The watchman executable has both the client and the server components of the watchman service. When running watchman, it will attempt to communicate with your existing server instance (each user has their own persistent process), and will attempt to start it if it doesn’t exist. There are some options that affect how watchman will locate the server, some options that affect only the client and some others that affect only the server. ... -
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Qwen3-Coder
Qwen3-Coder is the code version of Qwen3
Qwen3-Coder is the latest and most powerful agentic code model developed by the Qwen team at Alibaba Cloud. Its flagship version, Qwen3-Coder-480B-A35B-Instruct, features a massive 480 billion-parameter Mixture-of-Experts architecture with 35 billion active parameters, delivering top-tier performance on coding and agentic tasks. This model sets new state-of-the-art benchmarks among open models for agentic coding, browser-use, and tool-use, matching performance comparable to leading models... -
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Antigravity Awesome Skills
The Ultimate Collection of 700+ Agentic Skills for Claude Code
...Rather than focusing on production-grade systems, it provides creative and high-impact skills that demonstrate how agents can be used to automate tasks, generate content, assist with daily operations, or integrate into larger workflows with minimal configuration. The project includes skill definitions, example prompts, and usage patterns that highlight how modular abilities can be assembled into functioning assistants. Because it aims to reduce cognitive overhead, many skills show how to structure intents, handle context, and orchestrate multi-step reasoning without deep technical complexity. It also serves as inspiration for users looking to prototype new use cases — from conversational helpers that answer questions to workflow automators that trigger actions. -
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Tunix
A JAX-native LLM Post-Training Library
Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation,... -
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PandasAI
PandasAI is a Python library that integrates generative AI
...It is designed to be used in conjunction with pandas, and is not a replacement for it. PandasAI makes pandas (and all the most used data analyst libraries) conversational, allowing you to ask questions to your data in natural language. For example, you can ask PandasAI to find all the rows in a DataFrame where the value of a column is greater than 5, and it will return a DataFrame containing only those rows. -
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pandas-datareader
Extract data from a wide range of Internet sources
Up-to-date remote data access for pandas. Works for multiple versions of pandas. Install using pip and then import and use one of the data readers. This example reads 5-years of 10-year constant maturity yields on U.S. government bonds. Stable documentation is available on github.io. A second copy of the stable documentation is hosted on read the docs for more details. -
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Finance Database
This is a database of 300.000+ symbols containing Equities, ETFs, etc.
...Trying to understand what type of companies or ETFs are available is incredibly challenging with there being millions of companies and derivatives available on the market. Sure, the most traded companies and ETFs can quickly be found simply because they are known to the public (for example, Microsoft, Tesla, S&P500 ETF or an All-World ETF). However, what else is out there is often unknown. This database tries to solve that. It features 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets. It, therefore, allows you to obtain a broad overview of sectors, industries, types of investments and much more. ... -
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cheat.sh
The only cheat sheet you need
cheat.sh is a compact, network-accessible cheat-sheet service that serves concise examples and usage notes for hundreds of shell commands, programming languages, and tools via a simple HTTP interface. 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. ... -
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Superstaq
Quantum software platform that is optimized across the quantum stack
This repository is the home of the Superstaq development team's open-source work. Our quantum software platform is optimized across the quantum stack and enables users to write quantum programs in Cirq or Qiskit and target a variety of quantum computers and simulators. -
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xxh
Bring your favorite shell wherever you go through the ssh
...Security and host environment are a prime focus. No blindfold copying config files from local to the remote host. Following privacy and repeatability practices the best way is to fork the xxh plugin or shell example and pack your configs into it. Every xxh repo could be forked, customized, and reused without waiting for a package management system, xxh release, or any third-party packages. Five shells are currently supported and more could be added by the community. -
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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and supports both synchronous and asynchronous usage patterns depending on your application needs. ... -
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Manim Skills Repository
Agent skills for Manim to create 3Blue1Brown style animations
Manim Skills Repository provides a well-crafted set of “agent skills” and reusable components that make it easier to produce animations in Manim similar to the iconic style seen in 3Blue1Brown videos. It supplies templates, best-practice patterns, and example scenes that help users quickly get started with both Manim Community Edition and the older ManimGL framework, allowing for expressive mathematical and conceptual animations without reinventing the wheel. The project aims to wrap common animation logic into structured skills that can be invoked programmatically, reducing boilerplate and allowing creators to focus on creative content rather than low-level animation setup. ...
