Search Results for "example" - Page 33
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Showing 3182 open source projects for "example"
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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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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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Plugins Quickstart
Get a ChatGPT plugin up and running in under 5 minutes
plugins-quickstart is a starter project created by OpenAI to help developers build and deploy ChatGPT plugins quickly. It provides a minimal but complete example of how to structure a plugin, implement an API, and define the necessary configuration files. The repository demonstrates how a plugin can be served, authenticated, and integrated with ChatGPT for real-world use. By including both the backend code and plugin manifest, it guides developers through the end-to-end development workflow. ... -
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Matrix ChatGPT Bot
Talk to ChatGPT via any Matrix client
Matrix ChatGPT Bot allows you to talk to ChatGPT via any Matrix client. OpenAI released the official API for ChatGPT. Thus, we no longer have to use any older models or any models which kept on being turned off by OpenAI. This means the bot is now way more stable and way faster. However, please note: The usage of the API is no longer free. If you use this bot, your OpenAI account will be charged! You might want to limit your budget in your account using the OpenAI website. You need to remove... -
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RDD! USB HID Report Descriptor Decoder
Create C structures from USB HID Report Descriptors
This will read a USB Human Interface Device (HID) report descriptor from the specified input file then attempt to decode it and, optionally, create a C language header file from it. It also does some minimal sanity checks to verify that the report descriptor is valid. The input file can be a binary file or a text file (for example, an existing C header file). If it is a text file, it will concatenate all the printable-hex-like text that it finds on each line (until the first non-hex sequence is found) into a single string of hex digits, and then attempt to decode that string. You can feed it an existing C header file and it will decode it as long as you have all the hex strings (e.g. 0x0F, 0x0Fb2) at the beginning of each line. ... -
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SGE_GPU
Patch to SGE 2011.p1,Son of Grid Engine, multiple GPU, Linux
...This also works for parallel jobs. >qsub -pe openmpi 4 -l ngpus=1 ... Here, "-l ngpus=1" request 1 GPU for 1 process. It supports multiple GPU scheduling on nodes as well. For example, if node001 has 4 GPUs installed. JobA uses GPU0, JobB uses GPU2, and then JobC requestes 2 GPUs, it can dispatch GPU1 and GPU3 to JobC, and set the environment for the job on node001: CUDA_VISIBLE_DEVICES=1,3 For non-GPU jobs, it is set to empty. No loadsensor needed. Developed on CentOS 6.2, Kernel 2.6.32-220.2.1.el6.x86_64 This patch is only tested partially on a small simulating environment. ... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Deep Learning Models
A collection of various deep learning architectures, models, and tips
This repository collects clear, well-documented implementations of deep learning models and training utilities written by Sebastian Raschka. The code favors readability and pedagogy: components are organized so you can trace data flow through layers, losses, optimizers, and evaluation. Examples span fundamental architectures—MLPs, CNNs, RNN/Transformers—and practical tasks like image classification or text modeling. Reproducible training scripts and configuration files make it... -
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GPT Discord Bot
Example Discord bot written in Python that uses the completions API
GPT Discord Bot is an example project from OpenAI that shows how to integrate the OpenAI API with Discord using Python. The bot uses the Chat Completions API (defaulting to gpt-3.5-turbo) to carry out conversational interactions and the Moderations API to filter user messages. It is built on top of the discord.py framework and the OpenAI Python library, providing a simple, extensible template for building AI-powered Discord applications. -
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Easy Shopping Cart For All Shopkeepers
Better Customer Self Service With This Easy to Edit Spreadsheet FILE
Just download the above zip file, extract it and then view the README.txt file for instructions. Also, view the video / screenshots below for assistance. Notes: Out of Stock products are indicated with a disabled red color button. An example is included for this condition. Notes ii : Save the new index.html in the same folder as index_sample.html file. Tags : free shopping cart / POS (point-of-sale) software perfect for your retail store, restaurant, food truck, grocery store, beauty salon, car wash and more. -
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vimwiki
Personal Wiki for Vim
...Organize notes and ideas and quickly create links between them, manage todo-lists, and write a diary. VimWiki is a personal wiki for Vim, a number of linked text files that have their own syntax highlighting. See the VimWiki Wiki for an example website built with VimWiki! Three markup syntaxes supported, Vimwiki's own syntax, Markdown, MediaWiki. Export everything to HTML, link to other wiki pages and external files, search through all wiki pages. Outline notes and tasks in indented lists, quickly manipulate numbered and bulleted lists, tag wiki pages or arbitrary places and quickly jump to tags, abd auto-formatted tables. ... -
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OnnxStream
Lightweight inference library for ONNX files, written in C++
The challenge is to run Stable Diffusion 1.5, which includes a large transformer model with almost 1 billion parameters, on a Raspberry Pi Zero 2, which is a microcomputer with 512MB of RAM, without adding more swap space and without offloading intermediate results on disk. The recommended minimum RAM/VRAM for Stable Diffusion 1.5 is typically 8GB. Generally, major machine learning frameworks and libraries are focused on minimizing inference latency and/or maximizing throughput, all of which... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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nb2mail
Send a notebook as an email
This repo contains a jupyter nbconvert exporter to convert notebooks to multipart MIME, and a postprocessor to send it via smtp. nb2mail does not do anything by itself. It provides an export format ("mail") and postprocessor ("SendMailPostProcessor"). Please see the nbconvert documentation and example configuration for more information. -
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Crow Translate
Lightweight translator that allows you to translate and speak text
...Wayland does not support global shortcuts registration, but you can use D-Bus to bind actions in the system settings. For desktop environments that support additional applications actions (KDE, for example) you will see them predefined in the system shortcut settings. You can also use them for X11 sessions, but you need to disable global shortcuts registration in the application settings to avoid conflicts. On Linux to make the application look native on a non-KDE desktop environment, you need to configure Qt applications styling. -
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Graphtage
A semantic diff utility and library for tree-like files such as JSON
...Its name is a portmanteau of “graph” and “graftage”, the latter being the horticultural practice of joining two trees together such that they grow as one. Graphtage performs an analysis on an intermediate representation of the trees that is divorced from the filetypes of the input files. This means, for example, that you can diff a JSON file against a YAML file. Also, the output format can be different from the input format(s). By default, Graphtage will format the output diff in the same file format as the first input file. But one could, for example, diff two JSON files and format the output in YAML. There are several command-line arguments to specify these transformations, such as --format; please check the --help output for more information. -
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DeepSeek MoE
Towards Ultimate Expert Specialization in Mixture-of-Experts Language
DeepSeek-MoE (“DeepSeek MoE”) is the DeepSeek open implementation of a Mixture-of-Experts (MoE) model architecture meant to increase parameter efficiency by activating only a subset of “expert” submodules per input. The repository introduces fine-grained expert segmentation and shared expert isolation to improve specialization while controlling compute cost. For example, their MoE variant with 16.4B parameters claims comparable or better performance to standard dense models like DeepSeek 7B or LLaMA2 7B using about 40% of the total compute. The repo publishes both Base and Chat variants of the 16B MoE model (deepseek-moe-16b) and provides evaluation results across benchmarks. It also includes a quick start with inference instructions (using Hugging Face Transformers) and guidance on fine-tuning (DeepSpeed, hyperparameters, quantization). ... -
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SSD in PyTorch 1.0
High quality, fast, modular reference implementation of SSD in PyTorch
...Add your own modules without pain. We abstract backbone, Detector, BoxHead, BoxPredictor, etc. You can replace every component with your own code without changing the code base. For example, You can add EfficientNet as the backbone, just add efficient_net.py (ALREADY ADDED) and register it, specific it in the config file, It's done! Smooth and enjoyable training procedure: we save the state of model, optimizer, scheduler, training iter, you can stop your training and resume training exactly from the save point without change your training CMD. -
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ImplicitCAD
A math-inspired CAD program in haskell. CSG, bevels, and shells
...Generally, objects in programmatic CAD are built with Constructive Solid Geometry or CSG. Unions, intersections and differences of simpler shapes slowly build the object. ImplicitCAD supports all this and much more! For example, it provides rounded unions so that one can have smooth interfaces between objects. -
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YYeTsBot
Renren Film and Television bot, fully connected to Renren resources
...When searching for resources, it will be searched according to my predetermined priority (everyone video offline, subtitle man), of course, you can also use commands to force a subtitle group. Due to the difference in translations, it is recommended to enter a partial translation and then select from the list. For example, if you want to watch the fourth season of Game of Thrones, just search for "Game of Thrones". Want to keep a resource for yourself, but don't know how to program? It doesn't matter! There are currently two methods available, please choose according to your own situation. -
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Classnames
A simple javascript utility for conditionally joining classNames
...The utility is small and framework-agnostic, so it can be used in Node, browser code, or any bundler setup including Browserify and Webpack. It maintains backwards compatibility while evolving (for example, introducing polyfill requirements for older browsers in newer versions), and it ships with TypeScript bindings for better type safety. -
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Mixtral offloading
Run Mixtral-8x7B models in Colab or consumer desktops
Mixtral-Offloading is an open-source project designed to enable efficient inference of large Mixture-of-Experts language models such as Mixtral-8x7B on hardware with limited GPU memory. The project implements techniques that allow model components to be dynamically moved between CPU memory and GPU memory during inference, significantly reducing the amount of GPU VRAM required to run the model. This approach takes advantage of the sparse activation properties of mixture-of-experts... -
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Moment.js
Parse, validate, manipulate, and display dates in javascript
Moment is a JavaScript date and time library that simplifies parsing, formatting, arithmetic, and humanizing of dates. It supports many formats in input and output, internationalization (i18n), locale-based month/day names, relative time (for example, “3 days ago”), and chaining of operations (adding, subtracting, diffing). Developers often use it for calendar displays, scheduling, and manipulating times across time zones or daylight saving transitions. While it makes working with date strings convenient, moment maintains internal mutability, which has trade-offs with safety and chainability. ... -
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SVGEdit
Powerful SVG-Editor for your browser
...You can have a look to index.html to see how you can insert a div element into your HTML code and inject the editor into the div. The "svgcanvas" that takes care of the underlying svg edition. It can be used to build your own editor. See example in the demos folder or the svg-edit-react repository. -
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axflow
The TypeScript framework for AI development
...Its core SDK enables developers to integrate language model capabilities into web applications while maintaining strong modular design principles. Additional components support data ingestion, evaluation, and model interaction workflows that are commonly required when building production AI systems. For example, the framework includes modules for connecting application data to language models, evaluating the quality of model outputs, and building streaming user interfaces. Because each component can be used independently, developers can adopt Axflow incrementally rather than committing to a monolithic framework. This flexibility makes the system suitable for both experimentation and production environments. -
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Algorithm Visualizer
Interactive Online Platform that Visualizes Algorithms from Code
...The repo collects short programs (originally a set of shell and Ruby scripts) and many community contributed ports in other languages to show “how you might automate X” — for example sending a quick SMS, firing off an email, or triggering a coffee maker — with examples and scheduling snippets included. The README explains each example, lists required environment variables or credentials (e.g., Twilio/Gmail where applicable), and gives cron examples so readers can run the scripts in a real environment. The project is intentionally informal and educational: it’s meant for experimentation, learning language-interop, and having fun rather than production-grade automation. ... -
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py_automata
Virtual machines communicating over a virtual network.
By using virtual machines, known as workcells, to communicate with other virtual machines over a virtual network, creating complex event driven programs becomes very simple. For example, the USB port interface is completely autonomous and doesn't have an API. Instead, it interacts with other workcells by receiving three request messages, 'Read', 'Write' and 'Query' and transmitting 'Read' and 'Write' status messages. This is based on the industrial automation programming model where complex machines interact using communication methods as simple as relay contacts. -
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z
Tracks your most used directories, based on 'frecency'
Tracks your most used directories, based on 'frecency'. After a short learning phase, z will take you to the most 'frecent directory that matches ALL of the regexes given on the command line, in order. For example, z foo bar would match /foo/bar but not /bar/foo. The rank of directories maintained by z undergoes aging based on a simple formula. The rank of each entry is incremented every time it is accessed. When the sum of ranks is over 9000, all ranks are multiplied by 0.99. Entries with a rank lower than 1 are forgotten. Frecency is a portmanteau of 'recent' and 'frequency'. ... -
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Alpaca-CoT
We unified the interfaces of instruction-tuning data
Alpaca-CoT is an open research project focused on improving reasoning capabilities in language models through chain-of-thought training data. The project builds upon the Alpaca instruction-tuning approach by introducing datasets and methods that encourage models to produce intermediate reasoning steps when solving problems. Instead of generating answers directly, the model learns to produce logical reasoning sequences that lead to the final solution. This chain-of-thought supervision helps...
