Search Results for "can" - Page 16
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Showing 5119 open source projects for "can"
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Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. ... -
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EverOS
One portable memory layer for every AI agent
...It stores conversations, files, and agent trajectories as readable Markdown rather than hiding them only inside a database. Local SQLite and LanceDB indexes provide fast retrieval while the Markdown files remain the canonical source of truth. Memories can be edited, diffed, versioned with Git, and reused across tools and workflows. The system is designed to preserve user context and agent experience across sessions without forcing dependence on a hosted service. EverOS can serve as shared memory infrastructure for coding assistants, personal agents, and custom applications. Its architecture emphasizes user ownership, portability, and self-evolving reuse of accumulated knowledge. -
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claude-video
Give Claude the ability to watch any video
...The workflow checks captions first, downloads only what is necessary, extracts timestamped frames, and produces a transcript through native captions or Whisper fallback. It supports different detail levels so users can trade speed, token cost, and visual coverage depending on the task. The skill is useful for summarizing videos, reviewing screen recordings, analyzing content structure, diagnosing visual bugs, and turning course material into notes. It can be installed through Claude Code, agent skill hosts, claude.ai, or manual setup. -
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Edit Banana
Edit Banana: A framework for converting statistical figures
...Through AI-driven features like content-aware fill and stylistic adjustments, users can modify or replace regions of an image with contextually relevant content that blends seamlessly with the rest of the composition. -
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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AlphaFold 3
AlphaFold 3 inference pipeline
...The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling accurate modeling of proteins, ligands, and covalent modifications. Users can perform local predictions via Docker containers, integrating AlphaFold 3’s inference process with provided JSON input configurations. The software includes flexible options for running both data preprocessing and GPU-accelerated inference, allowing users to adapt to available computational resources. -
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QtAwesome
Iconic fonts in PyQt and PySide applications
...Use Font Awesome, Elusive Icons, Material Design Icons, Phosphor, Remix Icon or Microsoft's Codicons. QtAwesome comes bundled with Font Awesome, Elusive Icons, Material Design Icons, Phosphor, Remix Icon and Microsoft's Codicons but it can also be used with other iconic fonts. The load_font function allows loading other fonts dynamically. QtAwesome ships with a browser that displays all the available icons. You can use this to search for an icon that suits your requirements and then copy the name that should be used to create that icon. -
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Lightly
A python library for self-supervised learning on images
...We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. ... -
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Entity relation diagrams generator
Entity Relation Diagrams generation tool
...The simplest way to install eralchemy on OSX is by using Homebrew. ERAlchemy requires GraphViz to generate the graphs and Python. Both are available for Windows, Mac and Linux. Thanks to it's modular architecture, it can be connected to other ORMs/ODMs/OGMs/O*Ms. Some tests require a local postgres database with a schema named test in a database named test all owned by a user named postgres with a password of postgres. ERAlchemy was inspired by erd, though it is able to render the ER diagram directly from the database and not just only from the ER markup language. -
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TinyDB
Document oriented database optimized for you
...The target are small apps that would be blown away by a SQL-DB or an external database server. The current source code has 1800 lines of code (with about 40% documentation) and 1600 lines tests. Like MongoDB, you can store any document (represented as dict) in TinyDB. TinyDB is designed to be simple and fun to use by providing a simple and clean API. TinyDB neither needs an external server (as e.g. PyMongo) nor any dependencies from PyPI. TinyDB works on all modern versions of Python and PyPy. You can easily extend TinyDB by writing new storages or modify the behaviour of storages with Middlewares. ... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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xbar Plugins
Plugin repository for xbar (the BitBar reboot)
...It contains scripts, programs, and command-line tools that add quick status displays or interactive menu bar actions. The repository works as a centralized collection where users can find plugins for monitoring systems, services, development tools, productivity, and everyday utilities. Plugin authors can contribute their own scripts so others can install and use them through xbar. The project is practical because xbar can turn almost any script output into a menu bar item. It is best suited for macOS users who want lightweight, customizable, script-driven information in their menu bar. -
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SAFRS
SqlAlchemy Flask-Restful Swagger Json:API OpenAPI
SAFRS exposes SQLAlchemy database models as a JSON:API web service and generates the corresponding swagger/OpenAPI. Database objects such as the User class from the demo.py example can be extended to include relationships with other objects. The demo_relationship.py contains the following extension of the User class where a relationship with the Book class is implemented. -
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jsonschema
An implementation of the JSON Schema specification for Python
jsonschema is an implementation of the JSON Schema specification for Python. Full support for Draft 2020-12, Draft 2019-09, Draft 7, Draft 6, Draft 4 and Draft 3. Lazy validation that can iteratively report all validation errors. Programmatic querying of which properties or items failed validation. -
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Norfair
Lightweight Python library for adding real-time multi-object tracking
Norfair is a customizable lightweight Python library for real-time multi-object tracking. Using Norfair, you can add tracking capabilities to any detector with just a few lines of code. Any detector expressing its detections as a series of (x, y) coordinates can be used with Norfair. This includes detectors performing tasks such as object or keypoint detection. It can easily be inserted into complex video processing pipelines to add tracking to existing projects. ... -
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Masonite
The Modern And Developer Centric Python Web Framework
...Queue support to speed your application up by sending jobs to run on a queue or asynchronously. Notifications for sending notifications to your users simply and effectively. Task scheduling to run your jobs on a schedule (like everyday at midnight) so you can set and forget your tasks. Events you can listen for to execute listeners that perform your tasks when certain events happen in your app. A BEAUTIFUL Active Record style ORM called Masonite ORM. Amazingness at your fingertips. Many more features you need which you can find in the docs! -
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Isso
a Disqus alternative
Isso is a lightweight commenting server written in Python and JavaScript. It aims to be a drop-in replacement for Disqus. Users can edit or delete own comments (within 15 minutes by default). Comments in moderation queue are not publicly visible before activation. You can migrate your Disqus/WordPress comments without any hassle. Embed a single JS file, 40kb (12kb gzipped) and you are done. It allows anonymous comments, maintains identity and is simple to administrate. ... -
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Mozc
Mozc - a Japanese Input Method Editor designed for multi-platform
...While Mozc shares much of its codebase with Google’s internal IME, it operates as an independent open source project without official support, guarantees, or stable release cycles. Developers can build Mozc from source for their preferred platform, and the repository includes detailed build instructions for Android, Linux, macOS, and Windows environments. -
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Panda-Helper
Panda-Helper: Data profiling utility for Pandas DataFrames and Series
Panda-Helper is a simple data-profiling utility for Pandas DataFrames and Series. Assess data quality and usefulness with minimal effort. Quickly perform initial data exploration, so you can move on to more in-depth analysis. -
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Cookiecutter Django
Framework for jumpstarting production-ready Django projects quickly
...Docker support using docker-compose for development and production (using Traefik with LetsEncrypt support). Procfile for deploying to Heroku. Provides instructions for deploying to PythonAnywhere. You can run tests with unittest or pytest. -
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Cactus Needle
26m function call model that runs on incredibly small devices
...Needle is optimized for single-shot function calling rather than broad conversational ability, so its core use case is selecting the right tool and producing structured arguments. It can be fine-tuned locally, including on consumer machines, which makes it useful for experimentation with small personalized agents. The project is best suited for researchers and developers exploring tiny AI models, edge inference, and lightweight tool-calling systems. -
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Vulnhuntr
AI tool for detecting complex vulnerabilities in Python codebases
...Instead of scanning entire repositories at once, it builds call chains step by step, allowing deeper inspection of complex, multi-stage issues that traditional tools may miss. Vulnhuntr can generate detailed findings, including vulnerability explanations and potential exploit paths, helping developers and security teams understand risks faster. It supports multiple LLM providers such as OpenAI, Anthropic, and Ollama, and can be run via CLI, Docker, or pipx. Vulnhuntr is particularly useful for early-stage security reviews, bug bounty hunting, and auditing dependencies for hidden risks across open source projects. -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
...Pretrained checkpoints cover multiple model sizes so practitioners can trade accuracy for speed and memory depending on their deployment constraints. -
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Animated Drawings
Code to accompany "A Method for Animating Children's Drawings"
...The idea is that you draw a simple static figure (stick figure, silhouette, or contour lines), and the system produces plausible skeletal motion (walking, jumping, dancing) that adheres to the drawn shape constraints. The architecture separates shape embedding (to understand user-drawn geometry) from motion embedding / generation (to produce temporally coherent movement). Users can provide rough keyframes or control constraints (pose anchors), and the system fills intermediate frames with fluid animation. The repository includes demonstration apps and notebooks where you can upload or draw shapes and watch animations play. Because the approach is data-driven, it generalizes to new drawings even with varying proportions or stylizations. -
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Agent Skills
Specification and documentation for Agent Skills
agentskills is the specification and documentation repository for the Agent Skills open format, which defines a standardized way to package capabilities that AI agents can discover and use. A “skill” is treated as a foldered bundle containing instructions, optional scripts, and supporting resources, so agents can reliably apply a workflow or expertise area when it becomes relevant. The central goal is portability: you can write a skill once and reuse it across different agent runtimes and developer tools that implement the format. ... -
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NVIDIA NeMo
Toolkit for conversational AI
...NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI architectures are typically large and require a lot of data and compute for training. NeMo uses PyTorch Lightning for easy and performant multi-GPU/multi-node mixed-precision training. Supported models: Jasper, QuartzNet, CitriNet, Conformer-CTC, Conformer-Transducer, Squeezeformer-CTC, Squeezeformer-Transducer, ContextNet, LSTM-Transducer (RNNT), LSTM-CTC. ... -
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EasyOCR
Ready-to-use OCR with 80+ supported languages
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc. EasyOCR is a python module for extracting text from image. It is a general OCR that can read both natural scene text and dense text in document. We are currently supporting 80+ languages and expanding. Second-generation models: multiple times smaller size, multiple times faster inference, additional characters and comparable accuracy to the first generation models. EasyOCR will choose the latest model by default but you can also specify which model to use. ...
