Search Results for "performance" - Page 11
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Showing 1009 open source projects for "performance"
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Unstructured.IO
Open source libraries and APIs to build custom preprocessing pipelines
The unstructured library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of unstructured revolve around streamlining and optimizing the data processing workflow for LLMs. unstructured modular bricks and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and is efficient in transforming unstructured data into... -
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Torrra
A Python tool that lets you search and download torrents
Torrra is an open-source BitTorrent client and library focused on simplicity, performance, and extensibility for developers and self-hosted enthusiasts. It provides a command-line interface (CLI) and API that make it easy to add torrenting functionality to applications or automate downloads within scripts and workflows. The core of Torrra is built with modern asynchronous I/O and efficient resource handling, allowing it to manage multiple active torrents, peer connections, and swarm interactions without wasting CPU or memory. ... -
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Haystack
Haystack is an open source NLP framework to interact with your data
...Pick any Transformer model from Hugging Face's Model Hub, experiment, find the one that works. Use Haystack NLP components on top of Elasticsearch, OpenSearch, or plain SQL. Boost search performance with Pinecone, Milvus, FAISS, or Weaviate vector databases, and dense passage retrieval. -
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Gradio
Create UIs for your machine learning model in Python in 3 minutes
Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere! Gradio can be installed with pip. Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function. Gradio can be embedded in Python notebooks or presented as a webpage. A Gradio interface can automatically generate a public link you can share with colleagues that... -
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SenseVoice
Multilingual speech recognition and audio understanding model
...SenseVoice is trained on more than 400,000 hours of speech data and supports over 50 languages for multilingual recognition tasks. It is built to achieve high transcription accuracy while maintaining efficient inference performance. 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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SAM 3D Body
Code for running inference with the SAM 3D Body Model 3DB
SAM 3D Body is a promptable model for single-image full-body 3D human mesh recovery, designed to estimate detailed human pose and shape from just one RGB image. It reconstructs the full body, including feet and hands, using the Momentum Human Rig (MHR), a parametric mesh representation that decouples skeletal structure from surface shape for more accurate and interpretable results. The model is trained to be robust in diverse, in-the-wild conditions, so it handles varied clothing,... -
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CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
...Developed with MindSpore and later made PyTorch-compatible, it is capable of multilingual code generation, cross-lingual code translation, code completion, summarization, and explanation. It has been benchmarked on HumanEval-X, a multilingual program synthesis benchmark introduced alongside the model, and achieves state-of-the-art performance compared to other open models like InCoder and CodeGen. CodeGeeX also powers IDE plugins for VS Code and JetBrains, offering features like code completion, translation, debugging, and annotation. The model supports Ascend 910 and NVIDIA GPUs, with optimizations like quantization and FasterTransformer acceleration for faster inference. -
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MLX-Audio
A text-to-speech, speech-to-text and speech-to-speech library
...It focuses on text-to-speech and speech-to-speech workflows, with APIs and a command-line interface that make it easy to generate high-quality audio from text. Because it uses MLX and targets Apple Silicon, inference is fast and can take advantage of hardware acceleration and quantization for efficient on-device performance. The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. ... -
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JAX
Composable transformations of Python+NumPy programs
...But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python. -
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Audiblez
Generate audiobooks from e-books
Audiblez is a tool for generating high-quality .m4b audiobooks directly from .epub e-books using the Kokoro-82M neural text-to-speech model. It focuses on making audiobook creation easy and fast: from a single command, the tool splits an e-book into chapters, synthesizes audio for each section, and then merges the results into a structured audiobook with chapter-based WAV files and a final .m4b container. The Kokoro-82M model it uses is compact (82M parameters) yet natural sounding, trained... -
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Fantasy PL MCP
Fantasy Premier League MCP Server
Fantasy Premier League MCP Server is a Model Context Protocol (MCP) server that provides access to Fantasy Premier League (FPL) data and tools. It allows interaction with FPL data in MCP-compatible clients, enabling users to manage their fantasy teams effectively. -
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LightAutoML
Fast and customizable framework for automatic ML model creation
LightAutoML is an automated machine learning (AutoML) framework optimized for efficient model training and hyperparameter tuning, focusing on both tabular and text data. -
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BEIR
A Heterogeneous Benchmark for Information Retrieval
BEIR is a benchmark framework for evaluating information retrieval models across various datasets and tasks, including document ranking and question answering. -
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langrocks
Tools like web browser, computer access and code runner for LLMs
Langrocks is a programming language experimentation toolkit that enables developers to create, test, and optimize custom programming languages. -
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MagicTime
Time-lapse Video Generation Models as Metamorphic Simulators
This repository is the official implementation of MagicTime, a metamorphic video generation pipeline based on the given prompts. The main idea is to enhance the capacity of video generation models to accurately depict the real world through our proposed methods and dataset. Compared to general videos, metamorphic videos contain physical knowledge, long persistence, and strong variation, making them difficult to generate. -
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msgspec
A fast serialization and validation library, with builtin
msgspec is a fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML. -
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Sunfish
Sunfish: a Python Chess Engine in 111 lines of code
sunfish is a minimalist yet surprisingly strong chess engine written in Python, designed to demonstrate how powerful algorithms can be implemented in a highly compact codebase. Despite being only around a hundred lines of core logic, the engine achieves competitive performance, reaching ratings above 2000 on online platforms. It implements classic chess engine techniques such as alpha-beta pruning and efficient board representation while maintaining readability and simplicity. The project is often used as an educational tool for understanding game AI, search algorithms, and evaluation functions without the complexity of larger engines. ... -
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Numba CUDA Target
The CUDA target for Numba
...It allows users to define CUDA kernels using Python syntax, which are then compiled into efficient GPU code at runtime using LLVM-based toolchains. This approach significantly lowers the barrier to entry for GPU programming by eliminating the need to write CUDA C++ while still delivering high performance. The project supports the SIMT programming model, allowing developers to control threads, blocks, and memory hierarchies similarly to native CUDA programming. It is also used as a foundation for accelerating higher-level libraries such as RAPIDS, where custom user-defined GPU functions are required. The repository represents the continuation of CUDA support after its deprecation in core Numba, ensuring ongoing development and optimization under NVIDIA’s ecosystem. -
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MemOS
AI memory OS for LLM and Agent systems
...It aims to support advanced workflows like persistent in-memory data structures, crash-resilient state handling, and seamless sharing of data across tasks without copying. By abandoning some of the historical assumptions of Unix-style operating systems, MemOS attempts to unlock new performance and scalability tradeoffs for applications that need high throughput and low latency on memory-intensive workloads. -
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Qwen3-ASR
Qwen3-ASR is an open-source series of ASR models
Qwen3-ASR is an automatic speech recognition system in the QwenLM family, developed to convert spoken language into text with strong accuracy and real-time performance. As a specialized ASR variant of the broader Qwen language model ecosystem, it focuses on capturing reliable transcriptions from audio sources such as recordings, live streams, or conversational inputs while supporting low latency use cases. The architecture combines advanced neural acoustic modeling with context-aware language prediction so that outputs maintain both fidelity to the original speech and grammatical coherence. ... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous compute infrastructure. The project’s focus on extreme quantization dramatically reduces memory footprint and energy consumption compared with traditional 16-bit or 32-bit LLMs, making it practical to deploy advanced language understanding and generation models on everyday machines. ... -
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Saleor Commerce
A modular, high performance, headless e-commerce platform
An open-source, GraphQL-first e-commerce platform delivering ultra-fast, dynamic and personalized shopping experiences. A headless, GraphQL commerce platform delivering ultra-fast, dynamic, personalized shopping experiences. Beautiful online stores, anywhere, on any device. Saleor is a rapidly-growing open source e-commerce platform that has served high-volume companies from branches like publishing and apparel since 2012. Based on Python and Django, the latest major update introduces a... -
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armory
3D Engine with Blender Integration
Armory is an open-source 3D engine focused on portability, minimal footprint and performance. The renderer is fully scriptable with deferred and forward paths supported out of the box. Armory provides a full Blender integration add-on, turning it into a complete game development tool. The result is a unified workflow from start to finish. Powered by Armory engine, ArmorPaint is a stand-alone software designed for physically-based texture painting. -
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TensorFlow
TensorFlow is an open source library for machine learning
...TensorFlow expresses its computations as dataflow graphs, with each node in the graph representing an operation. Nodes take tensors—multidimensional arrays—as input and produce tensors as output. The framework allows for these algorithms to be run in C++ for better performance, while the multiple levels of APIs let the user determine how high or low they wish the level of abstraction to be in the models produced. Tensorflow can also be used for research and production with TensorFlow Extended. -
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Neuroglancer
WebGL-based viewer for volumetric data
...Neuroglancer operates entirely client-side, fetching data over HTTP in a variety of supported formats including Neuroglancer precomputed, N5, Zarr, and NIfTI, among others. The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools.
