Search Results for "common"
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Showing 183 open source projects for "common"
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1
Buzz
Buzz transcribes and translates audio offline
...Multiple Whisper backends, Transformer models, and GPU acceleration options provide flexibility across different computers. Transcripts can be searched, reviewed alongside playback, exported in common subtitle formats, automated through a CLI, or extended with plugins. -
2
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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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
how-to-optim-algorithm-in-cuda is an open educational repository focused on teaching developers how to optimize algorithms for high-performance execution on GPUs using CUDA. The project combines technical notes, code examples, and practical experiments that demonstrate how common computational kernels can be optimized to improve speed and memory efficiency. Instead of presenting only theoretical explanations, the repository includes hand-written CUDA implementations of fundamental operations such as reductions, element-wise computations, softmax, and attention mechanisms. These examples show how different optimization techniques influence performance on modern GPU hardware and allow readers to experiment with real implementations. ... -
4
TorchRec
Pytorch domain library for recommendation systems
...Pipelined training overlaps dataloading device transfer (copy to GPU), inter-device communications (input_dist), and computation (forward, backward) for increased performance. Optimized kernels for RecSys powered by FBGEMM. Quantization support for reduced precision training and inference. Common modules for RecSys. -
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5
SD.Next
All-in-one WebUI for AI generative image and video creation
...It also provides documentation and an ecosystem of guides that help users move from basic generation to more advanced usage patterns, including API-based automation. SD.Next is built to run across common desktop platforms and focuses on practicality: install, generate, iterate, and automate with minimal friction. -
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GPT-API-free
Free ChatGPT&DeepSeek API Key
...The system is designed to lower barriers for developers who want to test or build applications using conversational AI without managing billing or complex authentication flows. It supports common API formats similar to widely used AI services, making it easier to integrate into existing projects. The project is particularly useful for rapid prototyping, educational purposes, and lightweight applications. It also emphasizes ease of deployment, allowing users to set up and run the service quickly in different environments. -
7
KeepChatGPT
Browser userscript that enhances ChatGPT reliability and usability
...It runs through userscript managers and injects additional functionality directly into the page, allowing users to improve their workflow without requiring a backend service or separate application. It focuses on solving common problems experienced during AI conversations, such as session timeouts, network errors, message failures, and interruptions during long chats. By automating session refresh and maintaining active connections, KeepChatGPT reduces the need for repeated manual steps when recovering from errors or expired sessions. KeepChatGPT also introduces a variety of enhancements that improve the overall interface and user experience, including page cleanup, expanded display layouts, conversation cloning, and detailed chat information. -
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SenseVoice
Multilingual speech recognition and audio understanding model
...It includes different model variants optimized for either speed or accuracy, allowing developers to choose a configuration suitable for their use case. In addition to speech transcription, SenseVoice can detect emotional cues in speech and identify common sound events such as applause, laughter, or coughing. It also provides tools for running inference, exporting models to formats like ONNX or LibTorch, and deploying the system through APIs. -
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LlamaIndex
Central interface to connect your LLM's with external data
...It provides the following tools in an easy-to-use fashion. Provides indices over your unstructured and structured data for use with LLM's. These indices help to abstract away common boilerplate and pain points for in-context learning. Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when the context is too big. Offers you a comprehensive toolset, trading off cost and performance. -
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10
abogen
Generate audiobooks from EPUBs, PDFs and text with captions
...In other words, it automates the pipeline of reading a digital book (or document), converting its text into speech via a TTS engine, and packaging the result into an audiobook format — likely along with timestamped captions or subtitles that align with the spoken audio. This can be very useful for accessibility, content consumption on the go, or for users who prefer audio over reading. The repository supports handling common ebook formats and generating outputs that combine audio plus caption metadata. By automating text-to-speech for arbitrary documents, abogen reduces the friction of producing audiobooks and could be integrated into larger workflows (e.g., batch converting a library of texts). -
11
Agent Control
Centralized agent control plane for governing runtime agent behavior
...It is designed for production environments where organizations need observability, enforcement, and governance around autonomous or semi-autonomous AI systems. The repository includes SDKs, a server, telemetry components, examples, and integrations for common agent frameworks. It is especially useful for teams building customer-facing, internal, or enterprise agents that need scalable runtime guardrails. -
12
Cua
Open-source infrastructure for Computer-Use Agents. Sandboxes
Cua is an open-source command-line utility and workflow orchestrator designed to help developers define, compose, and run common tasks with a unified interface, promoting consistency and reuse across projects. It introduces a declarative syntax for specifying build scripts, automation pipelines, environment setups, and project-specific commands so contributors don’t need to memorize disparate scripts or tooling across languages and ecosystems. Cua can also manage task dependencies, handle cross-platform invocations, and simplify complex workflows into simple aliases or compound commands that are easy to share in teams. ... -
13
LiteLLM
lightweight package to simplify LLM API calls
Call all LLM APIs using the OpenAI format [Anthropic, Huggingface, Cohere, Azure OpenAI etc.] liteLLM supports streaming the model response back, pass stream=True to get a streaming iterator in response. Streaming is supported for OpenAI, Azure, Anthropic, and Huggingface models. -
14
LLaMA 3
The official Meta Llama 3 GitHub site
This repository is the former home for Llama 3 model artifacts and getting-started code, covering pre-trained and instruction-tuned variants across multiple parameter sizes. It introduced the public packaging of weights, licenses, and quickstart examples that helped developers fine-tune or run the models locally and on common serving stacks. As the Llama stack evolved, Meta consolidated repositories and marked this one deprecated, pointing users to newer, centralized hubs for models, utilities, and docs. Even as a deprecated repo, it documents the transition path and preserves references that clarify how Llama 3 releases map into the current ecosystem. ... -
15
GPUStack
Performance-optimized AI inference on your GPUs
...The platform supports GPUs from a wide range of vendors and can run on laptops, workstations, and servers across operating systems such as macOS, Windows, and Linux. It also enables developers to deploy models from common repositories like Hugging Face and access them through APIs similar to cloud-based AI services. -
16
TensorFlow
TensorFlow is an open source library for machine learning
Originally developed by Google for internal use, TensorFlow is an open source platform for machine learning. Available across all common operating systems (desktop, server and mobile), TensorFlow provides stable APIs for Python and C as well as APIs that are not guaranteed to be backwards compatible or are 3rd party for a variety of other languages. The platform can be easily deployed on multiple CPUs, GPUs and Google's proprietary chip, the tensor processing unit (TPU). ... -
17
AstronRPA
Agent-ready RPA suite with visual workflow automation tools engine
...It provides a visual workflow designer that supports low-code and no-code development, allowing users to create automation processes through a drag-and-drop interface instead of writing extensive code. It enables automation of common desktop software and browser-based tasks, making it suitable for repetitive business operations and system integrations. Astron RPA includes a large library of reusable components that handle tasks such as user interface operations, data processing, and system interactions, allowing workflows to be assembled from modular building blocks. ... -
18
ML-NLP
This project is a common knowledge point and code implementation
...The project is designed primarily as a learning resource for algorithm engineers and students preparing for technical interviews in machine learning or NLP roles. It compiles important concepts that frequently appear in machine learning discussions, including neural network architectures, training methods, and common algorithmic techniques. The repository also includes example implementations and explanatory materials that help readers understand the mechanics behind machine learning and NLP algorithms. In addition to technical explanations, the project organizes content into topic areas such as deep learning fundamentals, natural language processing techniques, and algorithm engineering practices. -
19
LangChain
⚡ Building applications with LLMs through composability ⚡
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
20
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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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph... -
22
Intel LLM Library for PyTorch
Accelerate local LLM inference and finetuning
...IPEX-LLM supports a wide range of popular models, including architectures such as LLaMA, Mistral, Qwen, and other transformer-based systems. The library can integrate with common AI frameworks and serving tools such as Hugging Face Transformers, LangChain, and vLLM, allowing developers to incorporate optimized inference into existing pipelines. -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. ... -
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DeepSeek Coder
DeepSeek Coder: Let the Code Write Itself
...Multiple sizes of the model are offered (e.g. 1B, 5.7B, 6.7B, 33B) so users can trade off inference cost vs capability. The repo provides model weights, documentation on training setup, evaluation results on common benchmarks (HumanEval, MultiPL-E, APPS, etc.), and inference tools. -
25
Pocket TTS
A TTS that fits in your CPU (and pocket)
Pocket TTS is a lightweight text-to-speech project designed to run efficiently on CPUs, targeting developers who want local speech generation without depending on GPUs or hosted web APIs. It is built to feel practical in everyday applications, where installation and usage should be as simple as adding a dependency and calling a function. The project focuses on keeping the runtime footprint manageable while still producing natural-sounding speech, which makes it attractive for offline tools,...
