Search Results for "common files"
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17 projects for "common files" with 2 filters applied:
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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kokoro-onnx
TTS with kokoro and onnx runtime
kokoro-onnx is a text-to-speech toolkit that wraps the Kokoro neural TTS model in an easy-to-use ONNX Runtime interface, so you can generate speech from Python with minimal setup. It focuses on running efficiently on commodity hardware, including macOS with Apple Silicon, while still delivering near real-time performance for many use cases. The project ships prebuilt model files and a simple example script, so you can go from installation to producing an audio.wav file in just a few steps.... -
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edge-tts
Use Microsoft Edge's online text-to-speech service from Python
...It wraps the same cloud voices used by Edge, exposing them through a simple CLI (edge-tts, edge-playback) and a Python API, so you can script high-quality speech generation in your own applications. The tool lets you list available voices, specify locale and voice name, and generate audio files in common formats like MP3 or WAV. It also supports generating subtitle files (such as SRT or VTT) alongside the speech, which is handy for video narration, e-learning, or accessibility workflows. From the CLI you can adjust parameters such as speaking rate, volume, and pitch, giving you some control over prosody without diving into SSML. ... -
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Microsoft Agent Skills
Skills, MCP servers, Custom Agents, Agents.md for SDKs
Microsoft Agent Skills is an actively maintained repository of skills, custom agents, templates, and MCP configuration files designed to extend AI coding assistants with deep knowledge about Azure SDKs and Microsoft AI Foundry services. The project bundles over a hundred domain-specific skills that teach AI agents how to perform tasks like Azure resource provisioning, SDK usage patterns, infrastructure setup, and common DevOps workflows, bridging the gap between agent reasoning and real-world Microsoft platform needs. ... -
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DeepSeek VL2
Mixture-of-Experts Vision-Language Models for Advanced Multimodal
...The model supports both image understanding (vision tasks) and multimodal reasoning, and is likely used as a component in agent systems to process visual inputs as context for downstream tasks. The repository includes evaluation results (e.g. image/text alignment scores, common VL benchmarks), configuration files, and model weights (where permitted). While the internal architecture details are not fully documented publicly, the repo suggests that VL2 introduces enhancements over prior vision-language models (e.g. better scaling, cross-modal attention, more robust alignment) to improve grounding and multimodal understanding. -
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Code2Prompt
Convert codebases into structured prompts optimized for LLM analysis
...It also respects common project conventions such as .gitignore, ensuring that unnecessary files are automatically excluded from the generated prompt. The generated output can be saved to a file, printed to standard output, or copied to the clipboard for immediate use. In addition to the core command line interface, the project also includes a library, Python bindings, and an MCP server. -
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MCP Toolbox for Databases
Open source MCP server that exposes database tools for AI agents
GenAI Toolbox, also known as MCP Toolbox for Databases, is an open source server designed to simplify how generative AI applications interact with databases. It provides a central service that exposes database operations as reusable tools that can be consumed by AI agents and developer workflows. It handles common infrastructure concerns such as authentication, connection pooling, and performance optimization so developers do not have to implement them individually in each application. By defining tools and data sources through configuration files, developers can standardize how AI systems access and operate on database resources. GenAI Toolbox is designed to integrate with agent frameworks and development environments so that AI assistants can execute database-related tasks with proper context and security. ... -
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Gemma in PyTorch
The official PyTorch implementation of Google's Gemma models
gemma_pytorch provides the official PyTorch reference for running and fine-tuning Google’s Gemma family of open models. It includes model definitions, configuration files, and loading utilities for multiple parameter scales, enabling quick evaluation and downstream adaptation. The repository demonstrates text generation pipelines, tokenizer setup, quantization paths, and adapters for low-rank or parameter-efficient fine-tuning. Example notebooks walk through instruction tuning and evaluation... -
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llama.vscode
VS Code extension for LLM-assisted code/text completion
...It integrates with the llama.cpp runtime to run language models locally, eliminating the need to rely entirely on external APIs or cloud providers. The extension supports common AI development features such as code completion, conversational chat assistance, and AI-assisted code editing directly within the IDE. Developers can select and manage models through a configuration interface that automatically downloads and runs the required models locally. The extension also supports agent-style coding workflows, where AI tools can perform more complex tasks such as analyzing project context or editing multiple files. -
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Anthony Fu's Skills
Anthony Fu's curated collection of agent skills
...The project serves as a curated registry of utilities that save time, standardize best practices, and encode expertise across domains, while still being easy to customize or extend. Contributors can add new skills following a common format, meaning the repository grows organically with community-driven capabilities. -
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LLM TLDR
95% token savings. 155x faster queries. 16 languages
...To enhance usability, LLM-TLDR includes command-line tools and integration examples for common workflows like batch summarization, webhook ingestion, and automation in documentation pipelines. -
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Lingvo
Framework for building neural networks
...Centralized hyperparameter configuration files allow researchers to share exact experiment setups so others can retrain and compare results reliably. -
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DeepSeek LLM
DeepSeek LLM: Let there be answers
The DeepSeek-LLM repository hosts the code, model files, evaluations, and documentation for DeepSeek’s LLM series (notably the 67B Chat variant). Its tagline is “Let there be answers.” The repo includes an “evaluation” folder (with results like math benchmark scores) and code artifacts (e.g. pre-commit config) that support model development and deployment. According to the evaluation files, DeepSeek LLM 67B Chat achieves strong performance on math benchmarks under both chain-of-thought (CoT)... -
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Common Resource Grep - crgrep
Common Resource Grep
CRGREP searches for matching text in databases, various document formats, archives and other difficult to access resources. A command line tool for name and content text matching in database tables, plain files, MS Office documents, PDF, archives, MP3 audio, image meta-data, scanned documents, maven dependencies and web resources. CRGREP will search resources within resources of any arbitrary combination or depth, so text within a document within a zip archive, and so on. Here you... -
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Deep-Learning-with-PyTorch-Tutorials
Deep Learning and PyTorch Introduction Video Tutorial with Source Code
Deep-Learning-with-PyTorch-Tutorials is a companion repository for an introductory deep learning course built around PyTorch. It provides source code, notebooks, and presentation materials for a practical video-based learning path. The lessons begin with PyTorch setup, tensors, indexing, mathematical operations, gradients, and basic optimization. They then move into neural networks, logistic regression, multilayer perceptrons, CNNs, ResNet, RNNs, LSTMs, autoencoders, VAEs, GANs, graph... -
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KMeansAniX
Animation of kmeans clustering using X Window System
Open source animation of kmeans clustering in X Window System using the C++ libplotter library. Supports Linux, Mac, and BSD. Includes common initialization methods such as Forgy, Macqueen, random, and angular. Sample videos are available through the Files Tab above. The SVN repo is accessible thorugh the Code Tab above. Requires a C++ compiler, libplot-dev, and libncurses5-dev Mac alternative to libplot-dev: macports plotutils +x11 -
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Open BEAGLE
Evolutionary Computation Framework in C++
Open BEAGLE is a C++ Evolutionary Computation (EC) framework. It provides an high-level software environment to do any kind of EC, with support for tree-based genetic programming; bit string, integer-valued vector, and real-valued vector genetic algorithms; and evolution strategy. The Open BEAGLE architecture follows strong principles of object oriented programming, where abstractions are represented by loosely coupled objects and where it is common and easy to reuse code. Open BEAGLE is... -
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A correlation detector that uses common sens. It can be used to derive information from log files for instance. It searches for the trigger and initial conditions of a user defined event. A sub-module of this project (called upamaana) can also be used as
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