Search Results for "language"
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Showing 1975 open source projects for "language"
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Classical Language Toolkit (CLTK)
The Classical Language Toolkit
The Classical Language Toolkit (CLTK) is a Python library offering natural language processing support for classical languages, including Latin, Greek, and others. -
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Recursive Language Models
General plug-and-play inference library for Recursive Language Models
RLM (short for Reinforcement Learning Models) is a modular framework that makes it easier to build, train, evaluate, and deploy reinforcement learning (RL) agents across a wide range of environments and tasks. It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom... -
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Natural Language Toolkit
NLTK Source
The Natural Language Toolkit (NLTK) is a widely used open-source Python library designed for working with human language data and building natural language processing (NLP) applications. It provides a comprehensive suite of modules, datasets, and tutorials that support both symbolic and statistical approaches to language processing. The toolkit includes implementations of many foundational NLP algorithms and utilities, enabling developers to perform tasks such as tokenization, stemming, parsing, classification, and semantic reasoning. ... -
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Google Research: Language
Shared repository for open-sourced projects from the Google AI Lang
Google Research: Language is a shared repository maintained by Google Research that contains open-source projects developed by the Google AI Language team. The repository hosts multiple subprojects related to natural language processing, machine learning, and large-scale language understanding systems. Many of the projects included in the repository correspond to research papers released by Google researchers and provide implementations of new NLP algorithms or experimental frameworks. ... -
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Prompt Declaration Language
Prompt Declaration Language is a declarative prompt programming lang
...Programming frameworks do not enforce or validate such structures since they are not specified in a machine-consumable way. The purpose of the Prompt Declaration Language (PDL) is to allow developers to specify the structure of prompts and to enforce it, while providing a unified programming framework for composing LLMs with rule-based systems. -
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llama.cpp Python Bindings
Python bindings for llama.cpp
llama-cpp-python provides Python bindings for llama.cpp, enabling the integration of LLaMA (Large Language Model Meta AI) language models into Python applications. This facilitates the use of LLaMA's capabilities in natural language processing tasks within Python environments. -
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BruteForceAI
Advanced LLM-powered brute-force tool combining AI intelligence
...The repository emphasizes features such as threaded execution, logging, and notification integrations, which position it as an automation-oriented project for controlled security assessment environments. From a software design perspective, its distinguishing idea is the use of language models as a front-end analysis layer that interprets a target page before the rest of the workflow proceeds. -
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clangd
clangd language server
clangd understands your C++ code and adds smart features to your editor: code completion, compile errors, definition, and more. clangd is a language server that can work with many editors via a plugin. Here’s Visual Studio Code with the clangd plugin, demonstrating code completion. -
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DeepSeek-V3
Powerful AI language model (MoE) optimized for efficiency/performance
DeepSeek-V3 is a robust Mixture-of-Experts (MoE) language model developed by DeepSeek, featuring a total of 671 billion parameters, with 37 billion activated per token. It employs Multi-head Latent Attention (MLA) and the DeepSeekMoE architecture to enhance computational efficiency. The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. -
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Synthetic Data Generator
SDG is a specialized framework
...This makes the generated data suitable for tasks such as machine learning model training, testing software systems, sharing datasets across organizations, and conducting research without violating privacy regulations. The system supports multiple generation methods including statistical models, generative adversarial networks, and large language model–based synthesis. It also includes a data processing module capable of handling different data types, preprocessing columns, managing missing values, and converting formats automatically before model training. -
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FFsubsync
Automagically synchronize subtitles with video
Language-agnostic automatic synchronization of subtitles with video, so that subtitles are aligned to the correct starting point within the video. First, make sure ffmpeg is installed. Make sure ffmpeg is on your path and can be referenced from the command line! Next, grab the script. It should work with both Python 2 and Python 3. There may be occasions where you have a correctly synchronized srt file in a language you are unfamiliar with, as well as an unsynchronized srt file in your native language. ... -
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Bonsai 27B
Run Bonsai (1-bit) and Ternary-Bonsai language models locally
Bonsai 27B is a repository for downloading, configuring, and running PrismML’s highly compressed Bonsai language models on local hardware. It supports the 1-bit Bonsai and higher-quality Ternary-Bonsai families in 1.7B, 4B, 8B, and 27B sizes. The models can run on macOS, Linux, and Windows through CPU, Metal, CUDA, Vulkan, ROCm, llama.cpp, or MLX backends. Its 27B models process text, images, screenshots, and PDFs while supporting reasoning and long-context conversations. -
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pandas
Fast, flexible and powerful Python data analysis toolkit
pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase. pandas is continuously being developed to be a fundamental high-level building block for doing practical, real world data analysis in Python, as well as powerful and flexible open source data analysis/ manipulation tool for any language. -
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Retrobios
Complete BIOS and firmware packs for RetroArch, Batocera, Recalbox
...It emphasizes simplicity and transparency, allowing developers to study and modify core boot processes at a granular level. The architecture is typically close to bare metal, requiring knowledge of assembly language and hardware interfaces. It may also serve as a foundation for building custom operating systems or experimenting with low-level system design. Overall, retrobios functions as a learning and experimentation platform for understanding foundational computing concepts. -
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GPT4All
Run Local LLMs on Any Device. Open-source
GPT4All is an open-source project that allows users to run large language models (LLMs) locally on their desktops or laptops, eliminating the need for API calls or GPUs. The software provides a simple, user-friendly application that can be downloaded and run on various platforms, including Windows, macOS, and Ubuntu, without requiring specialized hardware. It integrates with the llama.cpp implementation and supports multiple LLMs, allowing users to interact with AI models privately. ... -
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VideoCaptioner
AI-powered tool for generating, optimizing, and translating subtitles
VideoCaptioner is an open source AI-powered subtitle processing tool designed to simplify the workflow of creating subtitles for videos. It integrates speech recognition, language processing, and translation technologies to automatically generate and refine subtitles from video or audio sources. VideoCaptioner uses speech-to-text engines such as Whisper variants to transcribe spoken content and convert it into subtitle text with accurate timestamps. After transcription, large language models are used to intelligently restructure subtitles into natural sentences, correct wording, and improve readability for viewers. ... -
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Open Interpreter
A natural language interface for computers
Open Interpreter is an open-source tool that provides a natural-language interface for interacting with your computer. It lets large language models (LLMs) run code locally (Python, JavaScript, shell, etc.), enabling you to ask your computer to do tasks like data analysis, file manipulation, browsing, etc. in human terms (“chat with your computer”), with safeguards. Runs locally or via configured remote LLM servers/inference backends, giving flexibility to use models you trust or have locally. ... -
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DeepSeek R1
Open-source, high-performance AI model with advanced reasoning
DeepSeek-R1 is an open-source large language model developed by DeepSeek, designed to excel in complex reasoning tasks across domains such as mathematics, coding, and language. DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. -
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MarkPDFDown
A high-quality PDF to Markdown tool based on large language model
...The project focuses on extracting text, formatting, and structural information from complex PDF documents and transforming that information into clean Markdown that preserves the original hierarchy of headings, paragraphs, tables, and lists. By producing Markdown rather than raw text, the tool makes it easier to integrate documents into knowledge bases, documentation systems, or language model pipelines that rely on structured input. The software is particularly useful for developers working with technical documents, academic papers, or reports that need to be indexed, summarized, or processed by downstream AI systems. -
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Qwen
The official repo of Qwen chat & pretrained large language model
Qwen is a series of large language models developed by Alibaba Cloud, consisting of various pretrained versions like Qwen-1.8B, Qwen-7B, Qwen-14B, and Qwen-72B. These models, which range from smaller to larger configurations, are designed for a wide range of natural language processing tasks. They are openly available for research and commercial use, with Qwen's code and model weights shared on GitHub. -
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AirLLM
AirLLM 70B inference with single 4GB GPU
AirLLM is an open source Python library that enables extremely large language models to run on consumer hardware with very limited GPU memory. The project addresses one of the main barriers to local LLM experimentation by introducing a memory-efficient inference technique that loads model layers sequentially rather than storing the entire model in GPU memory. This layer-wise inference approach allows models with tens of billions of parameters to run on devices with only a few gigabytes of VRAM. ... -
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Anime Player
Video player for improving quality of hand-drawn images
A video player that enhances the quality of a hand-drawn image using Anime4K's high-performance scaling algorithm. This program is a video player written in the Python programming language using the PySimpleGUI graphical user interface library, an mpv media player, and the Anime4K scaling algorithm . Anime Player is designed to play video and audio files and includes functions such as opening files, URLs and folders, setting image scaling parameters using the Anime4K algorithm, creating an mpv config for watching videos using the Anime4K algorithm on Android, viewing help and information about tuning the algorithm. ... -
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SGLang
SGLang is a fast serving framework for large language models
SGLang is a fast serving framework for large language models and vision language models. It makes your interaction with models faster and more controllable by co-designing the backend runtime and frontend language. -
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RAPTOR
The official implementation of RAPTOR
RAPTOR is a retrieval architecture designed to improve retrieval-augmented generation systems by organizing documents into hierarchical structures that enable more effective context retrieval. Traditional RAG systems typically retrieve small text chunks independently, which can limit a model’s ability to understand broader document context. RAPTOR addresses this limitation by recursively embedding, clustering, and summarizing documents to create a tree-structured hierarchy of information.... -
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pyVideoTrans
Translate the video from one language to another and embed dubbing
pyVideoTrans is an ambitious open-source multimedia processing project that assembles speech recognition, subtitle generation, AI translation, voice synthesis, and video assembly into a unified pipeline for converting videos from one language to another with embedded dubbing and captions. At its core it runs speech-to-text models to transcribe audio tracks, translates the resulting text into a target language using local or cloud-based translation engines, synthesizes new speech to match the translated subtitles, and then merges that speech back into the video, creating a fully localized media file. ...
