Search Results for "can" - Page 84
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Showing 5020 open source projects for "can"
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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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MamoLinux
A customized Linux OS based on Ubuntu LTS release for All
...In a world full of OSes like Windows, Mac, or android, a laptop/computer cannot be called **my Laptop/computer/phone** unless I have full control over it both in software and hardware regime. Such freedom can only be enjoyed on Linux based OSes. Many Ubuntu/Debian-based OSes have been able create an user-friendly OS environment for intermediate computer users. However, they're still far more intimidating to my Li'l sister and Gramps compared to Windows. MamoLinux is a customized Linux-based(Ubuntu) Operating System and aims to achieve features like: 1. ... -
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SageMaker Inference Toolkit
Serve machine learning models within a Docker container
...The SageMaker Inference Toolkit implements a model serving stack and can be easily added to any Docker container, making it deployable to SageMaker. This library's serving stack is built on Multi Model Server, and it can serve your own models or those you trained on SageMaker using machine learning frameworks with native SageMaker support. -
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DALL-E 2 - Pytorch
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis
...Specifically, this repository will only build out the diffusion prior network, as it is the best performing variant (but which incidentally involves a causal transformer as the denoising network) To train DALLE-2 is a 3 step process, with the training of CLIP being the most important. To train CLIP, you can either use x-clip package, or join the LAION discord, where a lot of replication efforts are already underway. Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP. -
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PyMancala
PyMancala: A Python API for the Mancala game
PyMancala implements rules of the Mancala game, also called Awale. It can be played in different modes: human-human, human-computer or computer-computer. Different variants of the rules are implemented. Several 'basic' strategies are proposed for the human to get an advice and for the computer. Many others can be added and compared to the already existing ones. -
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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vits_chinese
Best practice TTS based on BERT and VITS
...VITS is a model combining variational autoencoders (VAEs), normalizing flows, adversarial learning, and a stochastic duration predictor — a design that enables generation of natural, expressive speech, capturing variations in rhythm and prosody. By customizing or porting VITS for Chinese, this project aims to produce high-quality TTS outputs in a language that can be challenging due to tones, pronunciation variability, and prosody. The repository offers full training and inference pipelines: preprocessing, mel-spectrogram generation, training scripts, and audio synthesis. For users who don’t train their own models, the project provides pre-trained checkpoints (or instructions) and expects integration with a vocoder during speech synthesis. -
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MaxFEM
Software for electromagnetic simulation
MaxFem is an open software package for electromagnetic simulation by using finite element methods. The package can solve problems in electrostatics, direct current, magnetostatics and eddy-currents. Since version 0.4.0, MaxFEM requires Python 3. We have moved the installers to the MaxFEM website (see below). In order to improve MaxFEM, we will require you to fill out a simple form before downloading them. -
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CoTracker
CoTracker is a model for tracking any point (pixel) on a video
CoTracker is a learning-based point tracking system that jointly follows many user-specified points across a video, rather than tracking each point independently. By reasoning about all tracks together, it can maintain temporal consistency, handle mutual occlusions, and reduce identity swaps when trajectories cross. The model takes sparse point queries on one frame and predicts their sub-pixel locations and a visibility score for every subsequent frame, producing long, coherent trajectories. Its transformer-style architecture aggregates information both along time and across points, allowing it to recover tracks even after brief disappearances. ... -
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State of Open Source AI
Clarity in the current fast-paced mess of Open Source innovation
...The goal of the project is to bring clarity to the rapidly evolving open-source AI ecosystem by documenting trends, models, tools, standards, deployment practices, and challenges. It acts as both a snapshot and a guide: readers can see what’s “hot now” in open AI infrastructure, what open licensing or governance issues are emerging, how deployment options compare, and what gaps remain. Because the AI domain moves quickly, part of the aim is to make the content maintainable and updateable by the community. The structure includes chapters or sections about model formats, evaluation benchmarks, hardware/backends, MLOps systems, alignment and safety issues, and open datasets. ... -
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Chinese Llama 2 7B
The first Chinese LLaMA2 model in the open source community
Chinese Llama 2 7B is an open-source large language model adapted from the LLaMA-2 architecture and optimized for Chinese and bilingual Chinese-English applications. The project provides a version of LLaMA-2 that has been further trained on Chinese data so it can better understand and generate text in Chinese while maintaining compatibility with the original model ecosystem. In addition to the model weights, the repository also includes supervised fine-tuning datasets and training resources that help developers build chat-optimized versions of the model. The project follows the input format used by the LLaMA-2 chat architecture, ensuring compatibility with existing optimization techniques and tools built for the LLaMA-2 ecosystem. ... -
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Autolabel
Label, clean and enrich text datasets with LLMs
Autolabel is a Python library to label, clean and enrich datasets with Large Language Models (LLMs). Autolabel data for NLP tasks such as classification, question-answering and named entity recognition, entity matching and more. Seamlessly use commercial and open-source LLMs from providers such as OpenAI, Anthropic, HuggingFace, Google and more. -
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ECMA-55 Minimal BASIC compiler
BASIC Compiler and Interpreter
John's Mutant contains several projects. The current project is an ECMA-55 Minimal BASIC compiler for Linux systems using AMD64 compatible CPUs. You can download the MinimalBASIC compiler source in the Files section. -
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Asteroid
The PyTorch-based audio source separation toolkit for researchers
...The default logger is TensorBoard in all the recipes. From the recipe folder, you can run the following to visualize the logs of all your runs. -
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bilili
Command-line Bilibili video and danmaku downloader with batch support
...It provides automated downloading capabilities that handle video streams and associated data efficiently while minimizing manual interaction. bilili supports retrieving both the video files and danmaku comments, which are the scrolling overlay comments commonly associated with the platform’s videos. These danmaku comments can be automatically converted into ASS subtitle format for playback compatibility with media players. bilili also implements multi-threaded and segmented downloading techniques to improve download performance and reliability. Additionally, it supports resuming interrupted downloads so partially downloaded content can continue without restarting from the beginning. -
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nmeasim
Simulate GPS+AIS sentences and send to a navigation SW
...These NMEA sentences simulate data coming from a GPS(sentence $GPRMC...) and an AIS receiver(sentence !AIVDM...) All the parameters : name, mmsi, initial position (lat/long), COG, SOG for my boat as well as for AIS targets, and I/O configuration (com port...) can be edited in the 'datasimul.json' (file created by the app with default values in V1.0) Just Download the nmeasim.exe file (green button above) and launch it. Be patient for a few seconds if you have a slow PC! Go to the 'Files' tab to look at the readme file and download any additional file if needed. -
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MMAction2
OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
...MMAction2 is an open-source toolbox for video understanding based on PyTorch. It is a part of the OpenMMLab project. Modular design: We decompose a video understanding framework into different components. One can easily construct a customized video understanding framework by combining different modules. Support four major video understanding tasks: MMAction2 implements various algorithms for multiple video understanding tasks, including action recognition, action localization, Spatio-temporal action detection, and skeleton-based action detection. ... -
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ChatFred
Alfred workflow using ChatGPT, DALL·E 2 and other models for chatting
.... ⤓ Install on the Alfred Gallery or download it over GitHub and add your OpenAI API key. If you have used ChatGPT or DALL·E 2, you already have an OpenAI account. Otherwise, you can sign up here - You will receive $5 in free credit, no payment data is required. Afterward you can create your API key. To start a conversation with ChatGPT either use the keyword cf, setup the workflow as a fallback search in Alfred or create your custom hotkey to directly send the clipboard content to ChatGPT. -
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ddgr
DuckDuckGo from the terminal
...While googler is highly popular among cmdline users, in many forums the need of a similar utility for privacy-aware DuckDuckGo came up. DuckDuckGo Bangs are super-cool too! So here's ddgr for you! Unlike the web interface, you can specify the number of search results you would like to see per page. It's more convenient than skimming through 30-odd search results per page. The default interface is carefully designed to use minimum space without sacrificing readability. ddgr isn't affiliated to DuckDuckGo in any way. Demo: https://asciinema.org/a/151849 -
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NExfil
Fast OSINT tool for discovering web profiles by username
...By performing automated queries across numerous services, NExfil helps investigators, researchers, and security professionals quickly identify potential accounts associated with a particular username. The tool focuses on delivering results rapidly while minimizing false positives during the search process. Users can supply a single username, multiple usernames, or a file containing a list of usernames for bulk scanning. NExfil processes these inputs and attempts to detect matching profiles across more than 350 websites within seconds. Because it is command-line based and open source, it can be easily integrated into OSINT workflows and cybersecurity research environments. -
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databooks
A CLI tool to reduce the friction between data scientists
databooks is a package to ease the collaboration between data scientists using Jupyter notebooks, by reducing the number of git conflicts between different notebooks and resolution of git conflicts when encountered. Simply specify the paths for notebook files to remove metadata. By doing so, we can already avoid many of the conflicts. Specify the paths for notebook files with conflicts to be fixed. Then, databooks finds the source notebooks that caused the conflicts and compares them (so no JSON manipulation!) Specify paths of notebooks to be checked, an expression or recipe of what you'd like to enforce. databooks will run your checks and raise errors if any notebook does not comply with the desired metadata values. ... -
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ReplitLM
Inference code and configs for the ReplitLM model family
...These models are designed specifically for coding workflows and are trained on large datasets of source code covering many programming languages and development environments. The repository also includes documentation and tutorials for integrating the models into development tools, APIs, or research pipelines. Developers can fine-tune the models using instruction-tuning techniques to adapt them for specific programming tasks or domains. The models were trained using modern deep learning techniques and large-scale GPU infrastructure to achieve strong performance in code completion and generation tasks. -
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PEP 8 Speaks
A GitHub app to automatically review Python code style
...Thus, new issues are overlooked and introduced in the project. PEP 8 Speaks can read the setup.cfg file and adopt your already existing flake8/pycodestyle settings. PEP 8 Speaks is free of cost. By default, it can not work on private repositories. -
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CostPal
CostPal is your personal finance manager
...CostPal Mobile is an additional application for your smartphone to interoperate with CostPal on your PC (currently available only for Android OS). With it's smooth intuitive interface (and by using it every day) you can spend minimum time required for tracking your personal expenses (less than 5 minutes a day!). It's purpose is to act as a scratchpad, not a standalone application for managing personal finance - for that you have CostPal. Currently only Dropbox is supported as a cloud storage used for data exchange. -
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Demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation
...The repository includes pretrained models for common tasks such as isolating vocals, drums, bass, and accompaniment from stereo music, achieving state-of-the-art results in benchmarks like MUSDB18. Demucs supports GPU-accelerated inference and can process multi-channel audio with chunked streaming for real-time or batch operation. It also provides training scripts and utilities to fine-tune on custom datasets, along with remixing and enhancement tools. -
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PyTorch Implementation of SDE Solvers
Differentiable SDE solvers with GPU support and efficient sensitivity
This library provides stochastic differential equation (SDE) solvers with GPU support and efficient backpropagation. examples/demo.ipynb gives a short guide on how to solve SDEs, including subtle points such as fixing the randomness in the solver and the choice of noise types. examples/latent_sde.py learns a latent stochastic differential equation, as in Section 5 of [1]. The example fits an SDE to data, whilst regularizing it to be like an Ornstein-Uhlenbeck prior process. The model can be loosely viewed as a variational autoencoder with its prior and approximate posterior being SDEs. The program outputs figures to the path specified by <TRAIN_DIR>. Training should stabilize after 500 iterations with the default hyperparameters. examples/sde_gan.py learns an SDE as a GAN, as in [2], [3]. The example trains an SDE as the generator of a GAN, whilst using a neural CDE [4] as the discriminator. -
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Super Easy AI Installer Tool
Application that simplifies the installation of AI-related projects
..."Super Easy AI Installer Tool" is currently in early development phase and may have a few bugs. But remains a great solution for users with minimal technical knowledge or expertise. Fixes underway. A tool that can generate animations and music from text, ideal for producing short videos and GIFs, as well as creating brief cinematic scenes.
