Search Results for "can" - Page 49
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Showing 5021 open source projects for "can"
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Fun Audio Chat
Large Audio Language Model built for natural interactions
Fun Audio Chat is an interactive voice-first conversational AI platform designed to let users engage in natural spoken dialogue with large language models in real time, turning speech into context-aware responses while maintaining a smooth back-and-forth experience. It combines speech recognition, audio processing, and AI generation so users can speak simply and receive spoken replies, enabling applications such as virtual assistants, voice bots, and hands-free chat interfaces. The system supports dynamic audio input and output, meaning it can handle different voices, tones, and conversational contexts without forcing users into typed interactions. With real-time streaming, it minimizes latency and delivers responses quickly, making it suitable for applications where responsiveness matters, such as interactive demos, accessibility tools, and conversational games. -
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CineCLI
CineCLI is a cross-platform command-line movie browser
...It connects to popular online movie databases to fetch metadata such as titles, release dates, ratings, genres, casts, posters, and plot summaries, presenting all of that in a concise, text-friendly format suitable for terminals or scripts. Users can search by keyword, year, or exact title and then drill into detailed views for individual films, making it useful for creating watchlists, learning more about films before watching, or integrating movie lookup into shell workflows. CineCLI also supports paginated results and filters so users can navigate large search outputs without overwhelming their screens. ... -
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Sygil WebUI
Stable Diffusion web UI
...It provides multiple UI modes (including a legacy Gradio interface) and focuses on making iterative prompting, parameter tuning, and post-processing accessible without writing code. The UI exposes core generation controls like resolution, CFG guidance, sampling steps, samplers, seeds, and batch generation so users can reproduce results and refine outputs systematically. It also supports jumping between workflows, such as sending an output directly into Image2Image for variations or into an “Image Lab” style area for enhancement and upscaling. Post-processing and enhancement are a major emphasis: the interface can route images through different upscalers and face-enhancement tools, helping users turn raw generations into cleaner, higher-resolution results. -
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ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to generate new views interactively. ... -
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Context Engineering Template
Context engineering is the new vibe coding
...By using this template, teams can ensure consistency across AI outputs, reduce errors that stem from contextual misunderstandings, and build reusable patterns. -
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4M
4M: Massively Multimodal Masked Modeling
...The design leans into flexibility and steerability, so prompts and masks can shape behavior without bespoke heads per task. In short, 4M provides a unified recipe to pretrain large multimodal models that generalize broadly while remaining practical to fine-tune. -
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ML Ferret
Refer and Ground Anything Anywhere at Any Granularity
Ferret is Apple’s end-to-end multimodal large language model designed specifically for flexible referring and grounding: it can understand references of any granularity (boxes, points, free-form regions) and then ground open-vocabulary descriptions back onto the image. The core idea is a hybrid region representation that mixes discrete coordinates with continuous visual features, so the model can fluidly handle “any-form” referring while maintaining precise spatial localization. ... -
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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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Napkin
An Infinitely Large Napkin
...The coverage spans undergraduate and early graduate topics, designed to show how different areas of math fit together—linear algebra, analysis, topology, number theory, and more—without going deeply into every subtopic. Because it is written in LaTeX (with supporting Asymptote or other tools), readers can compile their own version, and the repository integrates diagrams, flowcharts, and supplementary files. -
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Textual
Textual is a TUI (Text User Interface) framework for Python
...Textual adds interactivity to Rich with a Python API inspired by modern web development. On modern terminal software (installed by default on most systems), Textual apps can use 16.7 million colors with mouse support and smooth flicker-free animation. A powerful layout engine and re-usable components makes it possible to build apps that rival the desktop and web experience. Textual runs on Linux, macOS, and Windows. Textual requires Python 3.7 or above. The addition of [dev] installs Textual development tools. ... -
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AWS ParallelCluster Node
Python package installed on the Amazon EC2 instances
...It automatically sets up the required compute resources and a shared filesystem and offers a variety of batch schedulers such as AWS Batch and Slurm. AWS ParallelCluster facilitates both quick start proof of concepts (POCs) and production deployments. You can build higher-level workflows, such as a Genomics portal that automates the entire DNA sequencing workflow, on top of AWS ParallelCluster. -
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TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models are suitable. A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. ... -
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TensorBoardX
tensorboard for pytorch (and chainer, mxnet, numpy, etc.)
...It adds a lot of functionality on top of tensorboard such as dataset management, diffing experiments, seeing the code that generated the results and more. Create special chart by collecting charts tags in ‘scalars’. Note that this function can only be called once for each SummaryWriter() object. Because it only provides metadata to tensorboard, the function can be called before or after the training loop. -
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OpenAI Privacy Filter
Bidirectional token-classification model for identifiable info
...It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. The model supports long-context inputs, allowing it to analyze extensive documents without chunking, which improves consistency in redaction tasks. It can run locally on standard hardware, ensuring that sensitive information never leaves the user’s environment and supporting privacy-first workflows. The system is fine-tunable, enabling adaptation to specific datasets or compliance requirements across industries. It identifies multiple categories of sensitive data such as names, emails, and credentials, replacing them with placeholders to preserve structure. -
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Frontend Slides
Create beautiful slides on the web using Claude's frontend skills
Frontend Slides is a lightweight tool that enables users to create visually appealing, animation-rich web presentations without requiring knowledge of CSS or JavaScript by leveraging a guided, interactive workflow. It operates on a “show, don’t tell” philosophy, generating visual previews of styles so users can select their preferred design rather than describing it abstractly. The system produces fully self-contained HTML presentations with inline CSS and JavaScript, eliminating the need for external dependencies, build tools, or frameworks. It also supports converting existing PowerPoint files into web-based presentations while preserving content such as images, text, and structure. ... -
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Dagger
Containerized automation engine for programmable CI/CD workflows
...Dagger provides a core execution engine and system API that orchestrates containers, filesystems, secrets, repositories, and other resources needed during development pipelines. Developers can write pipelines using SDKs available for multiple programming languages, enabling integration with existing development stacks and tools. It focuses on repeatability and efficiency by running tasks incrementally and caching intermediate results so that only affected operations are re-executed when changes occur. -
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verl-agent
Designed for training LLM/VLM agents via RL
...This step-wise interaction model makes it possible to train agents to operate in long-horizon scenarios where decisions depend on cumulative context and previous outcomes. Developers can configure memory modules that determine how historical information is stored and incorporated into each step of the reasoning process. -
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cloud_enum
Multi-cloud OSINT tool for discovering public cloud resources
...It works by taking user-provided keywords and generating variations through mutation wordlists, then testing these combinations against common cloud service naming patterns. cloud_enum performs both HTTP probing and DNS lookups to identify resources such as storage buckets, cloud applications, and databases that may be exposed or accessible. cloud_enum uses concurrent processing to speed up scanning, enabling efficient enumeration of large numbers of possible resource names. It can identify both publicly accessible and protected resources, helping security researchers understand the external cloud footprint of an organization. -
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Agentic Context Engine
Make your agents learn from experience
...The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and curation, enabling agents to refine strategies across repeated tasks. In this workflow, one component generates solutions, another reflects on outcomes, and a third curates useful knowledge so it can be reused in future interactions. This architecture allows agents to gradually build persistent operational memory without requiring additional training datasets or model retraining. -
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OmAgent
Build multimodal language agents for fast prototype and production
OmAgent is an open-source Python framework designed to simplify the development of multimodal language agents that can reason, plan, and interact with different types of data sources. The framework provides abstractions and infrastructure for building AI agents that operate on text, images, video, and audio while maintaining a relatively simple interface for developers. Instead of forcing developers to implement complex orchestration logic manually, the system manages task scheduling, worker coordination, and node optimization behind the scenes. ... -
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DocETL
A system for agentic LLM-powered data processing and ETL
...Instead of relying on single prompts or ad-hoc scripts, DocETL provides a declarative pipeline framework that breaks complex document analysis tasks into manageable operations that can be optimized and orchestrated automatically. Pipelines are typically defined using a low-code YAML interface, giving users full control over prompts and processing steps while still simplifying workflow creation. -
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Skill Scanner
Security Scanner for Agent Skills
...It acts as a scanner that inspects Agent Skills packages to flag structural problems, inconsistencies, or security flaws before they are deployed or integrated into agent workflows. Because agent skills can contain executable instructions and logic, scanning them for risky patterns is essential to prevent inadvertent exploitation when used by intelligent systems. The tool supports maintainers and community contributors in automating quality checks and enforcing conventions across skill sets in a standardized way. While still evolving with contributions and issue discussions, it shows the community’s interest in building safer AI ecosystems around reusable capabilities. ... -
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JS Analyzer
Burp Suite extension for JavaScript static analysis
...The extension is designed to reduce manual effort when analyzing large or obfuscated JavaScript assets, helping testers find security vulnerabilities and sensitive information faster and more reliably. It also includes UI features such as live search, result filtering, and the ability to export findings in JSON format for further processing. The underlying engine can be used independently in Python, enabling integration into custom workflows or automated pipelines outside Burp Suite. -
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Orpheus TTS
Towards Human-Sounding Speech
...The project ships both pretrained and finetuned English models, as well as a family of multilingual models released as a research preview, and includes data-processing scripts so users can train or finetune their own variants. Inference is provided through a Python package that uses vLLM under the hood for high-throughput, low-latency generation, including streaming examples that show how to generate audio chunks in real time. The maintainers provide Colab notebooks, a standardized prompting format, and one-click deployment via Baseten for production-grade, FP8/FP16 optimized inference with ~200 ms streaming latency. -
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Pearl
A Production-ready Reinforcement Learning AI Agent Library
...Tutorials demonstrate end-to-end workflows on OpenAI Gym tasks and contextual-bandit setups derived from tabular datasets, emphasizing reproducibility and clear baselines. Pearl’s design favors clarity and deployability: metrics, logging, and evaluation harnesses are integrated so you can monitor learning, compare agents, and catch regressions.
