Showing 5116 open source projects for "can"

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    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

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    Veeam Data Platform v13.1

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  • 1
    cloud-morph

    cloud-morph

    Decentralize, Self-host Cloud Gaming/Application

    ...It leverages containerization and distributed architecture to handle workloads efficiently across multiple nodes. cloud-morph focuses on flexibility, enabling users to define custom processing pipelines for different media scenarios. It can be used for applications such as streaming, video processing, and content delivery optimization. Overall, it provides a scalable solution for handling multimedia transformations in cloud environments.
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  • 2
    TabPFN

    TabPFN

    Foundation Model for Tabular Data

    TabPFN is an open-source machine learning system that introduces a foundation model designed specifically for tabular data analysis. The model is based on transformer architectures and implements a prior-data fitted network that can perform supervised learning tasks such as classification and regression with minimal configuration. Unlike many traditional machine learning workflows that require extensive hyperparameter tuning and training cycles, TabPFN is pre-trained to perform inference directly on tabular datasets. This allows it to generate predictions extremely quickly, often within seconds, while maintaining competitive accuracy on small and medium-sized datasets. ...
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  • 3
    Claude Quickstarts

    Claude Quickstarts

    A collection of projects for building deployable applications

    Claude Quickstarts is a curated collection of starter projects and templates that help developers quickly begin building applications with the Claude API, making it easier to leverage Anthropic’s Claude models for real use cases. Each quickstart provides a foundational codebase with preconfigured settings and examples for common deployment scenarios, so developers can focus on customizing functionality instead of bootstrapping infrastructure. The repository includes demos, sample integrations, and instructions to get environments running with minimal setup while handling authentication, API calls, and error handling best practices. Because it’s designed as a learning and prototyping resource, Claude Quickstarts supports exploration of interactive applications, backend services, and workflows that benefit from large language model capabilities.
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  • 4
    Fara-7B

    Fara-7B

    An Efficient Agentic Model for Computer Use

    ...Rather than relying on ad-hoc or manual review processes, FARA enables organizations to profile AI behavior using standardized tests, metrics, and reporting templates, making evaluations reproducible and comparable over time. The framework supports plugin-based modules that can be tailored to industry-specific concerns or regulatory requirements, helping compliance teams, auditors, and engineers collaborate on shared assessment goals.
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    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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  • 5
    nbdev

    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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  • 6
    OAuthLib

    OAuthLib

    A generic, spec-compliant, thorough implementation of the OAuth

    A generic, spec-compliant, thorough implementation of the OAuth request-signing logic for Python 3.8+. OAuthLib is a framework which implements the logic of OAuth1 or OAuth2 without assuming a specific HTTP request object or web framework. Use it to graft OAuth client support onto your favorite HTTP library, or provide support onto your favourite web framework. If you're a maintainer of such a library, write a thin veneer on top of OAuthLib and get OAuth support for very little effort.
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  • 7
    GraalPy

    GraalPy

    A Python 3 implementation built on GraalVM

    GraalPy is a high-performance implementation of the Python language for the JVM built on GraalVM. GraalPy is a Python 3.11 compliant runtime. It has first-class support for embedding in Java and can turn Python applications into fast, standalone binaries. GraalPy is ready for production running pure Python code and has experimental support for many popular native extension modules.
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  • 8
    Slack Machine

    Slack Machine

    A simple, yet powerful and extendable Slack bot

    ...More than just a bot, Slack Machine is a framework that helps you develop your Slack workspace into a ChatOps powerhouse. Slack Machine is built with an intuitive plugin system that lets you build bots quickly but also allows for easy code organization. A plugin can look as simple as this:
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  • 9
    Agently

    Agently

    AI Agent Application Development Framework

    ...Enhance AI Agent using plugins instead of rebuilding a whole new agent. Agently is a development framework that helps developers build AI agent native applications really fast. You can use and build AI agents in your code in an extremely simple way.
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    Train ML Models With SQL You Already Know

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  • 10
    Intel Extension for PyTorch

    Intel Extension for PyTorch

    A Python package for extending the official PyTorch

    Intel® Extension for PyTorch* extends PyTorch* with up-to-date features optimizations for an extra performance boost on Intel hardware. Optimizations take advantage of Intel® Advanced Vector Extensions 512 (Intel® AVX-512) Vector Neural Network Instructions (VNNI) and Intel® Advanced Matrix Extensions (Intel® AMX) on Intel CPUs as well as Intel Xe Matrix Extensions (XMX) AI engines on Intel discrete GPUs. Moreover, Intel® Extension for PyTorch* provides easy GPU acceleration for Intel...
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  • 11
    Pretty Jupyter

    Pretty Jupyter

    Creates dynamic html report from jupyter notebook.

    Pretty Jupyter is an easy-to-use package that allows to create beautiful & dynamic HTML reports. Most of the features require little to no work to get working and greatly improve the quality of the output report, or even the developer’s comfort when creating the report. For example, tabs make some visualizations much more comfortable. The features are integrated directly into the output page, therefore there is no need to have an interpreter running in the backend. This makes the HTML easily...
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  • 12
    voila

    voila

    Voilà turns Jupyter notebooks into standalone web applications

    ...It is secure and customizable, giving you control over what your readers experience. Unlike the usual HTML-converted notebooks, each user connecting to the Voilà tornado application gets a dedicated Jupyter kernel which can execute the callbacks to changes in Jupyter interactive widgets. To render the bqplot example notebook as a standalone app, run voila bqplot.ipynb. To serve a directory of jupyter notebooks, run voila with no argument.
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  • 13
    Remarshal

    Remarshal

    Convert between CBOR, JSON, MessagePack, TOML, and YAML

    Convert between CBOR, JSON, MessagePack, TOML, and YAML. When installed, provides the command-line command remarshal as well as the short commands {cbor,json,msgpack,toml,yaml}2{cbor,json,msgpack,toml,yaml}. You can perform format conversion, reformatting, and error detection using these commands. CBOR, MessagePack, and YAML with binary fields cannot be converted to JSON or TOML. Binary fields are converted between CBOR, MessagePack, and YAML.
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  • 14
    spacy-llm

    spacy-llm

    Integrating LLMs into structured NLP pipelines

    Large Language Models (LLMs) feature powerful natural language understanding capabilities. With only a few (and sometimes no) examples, an LLM can be prompted to perform custom NLP tasks such as text categorization, named entity recognition, coreference resolution, information extraction and more. This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for fast prototyping and prompting, and turning unstructured responses into robust outputs for various NLP tasks, no training data required.
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  • 15
    DB-GPT

    DB-GPT

    Revolutionizing Database Interactions with Private LLM Technology

    DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure.
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  • 16
    TorchMetrics

    TorchMetrics

    Machine learning metrics for distributed, scalable PyTorch application

    TorchMetrics is a collection of 80+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. Your data will always be placed on the same device as your metrics. You can log Metric objects directly in Lightning to reduce even more boilerplate. The module-based metrics contain internal metric states (similar to the parameters of the PyTorch module) that automate accumulation and synchronization across devices! Automatic accumulation over multiple batches. Automatic synchronization between multiple devices. ...
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  • 17
    web.py

    web.py

    Web framework for python that is as simple as it is powerful

    web.py is a web framework for Python that is as simple as it is powerful. web.py is in the public domain, you can use it for whatever purpose with absolutely no restrictions. web.py was originally published while Aaron Swartz worked at reddit.com, where the site used it as it grew to become one of the top 1000 sites according to Alexa and served millions of daily page views. “It’s the anti-framework framework. web.py doesn’t get in your way,” explained founder Steve Huffman.
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  • 18

    Python Fire

    Automatically generate CLIs from absolutely any Python object

    Python Fire is a library that automatically generates command line interfaces (CLIs) from absolutely any Python object. It’s a really simple and easy way to create CLI in Python, and can also enable you to explore existing code or turn other people’s code into a CLI. Python Fire lets you call Fire on any Python object: be it functions, classes, objects, modules, lists-- you name it! It will help you develop as well as debug Python code, and make transitioning between Bash and Python a whole lot easier.
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  • 19
    UniMate

    UniMate

    UniMate: One Unified Model to Animate Diverse Skeletons

    ...Its topology-aware diffusion transformer conditions generation on skeleton structure rather than requiring a fixed character template. The accompanying UniML3D dataset contains 13,006 text-paired motion sequences with unified skeletal canonicalization. Inference can generate motion for unseen skeleton topologies without per-skeleton retraining or test-time optimization. The same model supports text-guided motion editing, in-betweening, and longer motion expansion. Training, inference, data processing, and preview checkpoints are provided for research use.
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  • 20
    MSA: Memory Sparse Attention

    MSA: Memory Sparse Attention

    Trainable latent-memory framework for 100M-token contexts

    ...Document-wise rotary position encoding and top-k routing keep training and inference close to linear complexity. A tiered KV-cache design stores routing keys on GPU while larger content states can remain on CPU. Its Memory Parallel engine distributes scoring and transfers only selected memory back to the accelerator. Memory Interleave alternates retrieval, context expansion, and generation to improve multi-hop reasoning across distant segments. The project reports experiments extending from 16K to 100M tokens, including inference on two A800 GPUs.
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  • 21
    Claude-Red

    Claude-Red

    claude-red is a curated library of offensive security skills

    ...The library covers web applications, identity, Active Directory, wireless systems, cloud environments, mobile platforms, embedded devices, reconnaissance, exploit research, and fuzzing. Skills load on demand from conversational triggers instead of occupying context continuously. Users can install the complete collection or select individual categories. The project is intended for legitimate red-team engagements, bug-bounty triage, CTF practice, operator training, and security research. Its modular structure makes the collection expandable as new methodologies and categories are added.
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  • 22
    learn_python3_spider

    learn_python3_spider

    Python crawler tutorial series, learning Python crawlers from 0 to 1

    ...It introduces request capture, browser and mobile traffic inspection, and core scraping libraries such as Requests, BeautifulSoup, Selenium, Appium, and Scrapy. Lessons also cover JSON parsing, regular expressions, concurrency, proxy usage, login handling, and CAPTCHA-related techniques. Data can be stored with CSV, MySQL, or MongoDB examples. More advanced material explores anti-scraping defenses, JavaScript analysis, WebSocket data, and distributed crawlers. The repository includes practical source-code examples for scraping several real-world websites and services.
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  • 23
    NeMo Automodel

    NeMo Automodel

    Pytorch Distributed native training library for LLMs/VLMs

    ...YAML recipes and CLI overrides keep experiments concise while preserving reproducibility. The library supports composable parallelism, optimized kernels, MoE acceleration, mixed precision, sequence packing, and asynchronous checkpointing. Jobs can run through interactive environments, Slurm, SkyPilot, or Kubernetes-based workflows. It targets both rapid research experiments and high-performance large-scale fine-tuning.
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  • 24
    smart_open

    smart_open

    Utils for streaming large files (S3, HDFS, gzip, bz2...)

    ...It acts as an extended replacement for Python's built-in open function. Supported backends include Amazon S3, Google Cloud Storage, Azure Blob Storage, HDFS, WebHDFS, HTTP, HTTPS, SFTP, and local filesystems. Data can be read or written without first downloading an entire remote object to disk. Transparent compression and decompression are supported for multiple common formats. Standard operations such as context managers, iteration, and supported seek behavior remain available. Optional transport dependencies let installations include only the cloud or protocol integrations an application actually requires.
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  • 25
    Zipline Reloaded

    Zipline Reloaded

    Zipline, a Pythonic Algorithmic Trading Library

    ...Common statistics such as moving averages and linear regression are available within algorithm workflows. Pandas-based input and output integrate naturally with the broader Python data-science ecosystem. Strategies can also use libraries such as SciPy, Matplotlib, statsmodels, and scikit-learn for analysis and modeling. The maintained fork updates dependencies and compatibility so the established Zipline workflow remains usable on modern Python environments.
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