Search Results for "machine language" - Page 7
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Showing 890 open source projects for "machine language"
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KuzuDB
Embeddable property graph database management system
KuzuDB is a high-performance graph database optimized for analytical queries, built from the ground up with a columnar storage engine. It is designed to efficiently process large-scale graph workloads, making it ideal for data science, machine learning, and knowledge graph applications. -
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ToolUniverse
Democratizing AI scientists with ToolUniverse
ToolUniverse is a comprehensive open-source ecosystem designed to transform any large language model into an autonomous “AI scientist” capable of performing real scientific research tasks through structured tool interaction. It standardizes how AI systems discover, select, and execute tools by introducing a unified AI-Tool Interaction Protocol that allows models to seamlessly connect with hundreds of scientific resources, including machine learning models, datasets, APIs, and analytical packages. ... -
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Memgraph
Open-source graph database, tuned for dynamic analytics environments
A high-performance, in-memory graph database designed for real-time analytics and complex network data processing. -
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Learning Interpretability Tool
Interactively analyze ML models to understand their behavior
The Learning Interpretability Tool (LIT, formerly known as the Language Interpretability Tool) is a visual, interactive ML model-understanding tool that supports text, image, and tabular data. It can be run as a standalone server, or inside of notebook environments such as Colab, Jupyter, and Google Cloud Vertex AI notebooks. -
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Fanyi
A 🇨🇳 and 🇺🇸 translate tool in your command line
Fanyi is a tool for translating words between the Chinese and English languages, right in your command line. It’s a good supportive tool for learning and reading the Chinese language from English, or the other way around. All translation data is fetched from iciba.com and fanyi.youdao.com, and with each translation comprehensive and related samples are given for better understanding and proper usage. There are translations for words as well as sentences, and in Mac/Linux bash, words can even... -
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MetaScreener
AI-powered tool for efficient abstract and PDF screening
...The system helps researchers analyze large collections of academic abstracts and research papers to determine which studies are relevant for inclusion in evidence synthesis projects. Instead of manually reviewing hundreds or thousands of documents, researchers can use MetaScreener to apply machine learning techniques that assist with classification and prioritization of candidate papers. The platform can analyze both abstracts and full PDF documents, enabling automated filtering based on research criteria defined by the user. By incorporating natural language processing techniques, the system can identify potentially relevant studies and reduce the workload associated with manual screening. -
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Korvus
Korvus is a search SDK that unifies the entire RAG pipeline
Korvus is an open-source retrieval-augmented generation (RAG) pipeline designed to run entirely inside PostgreSQL, allowing developers to build AI search and knowledge systems directly within a database environment. The project consolidates the typical steps of a RAG pipeline—including embedding generation, document retrieval, reranking, and text generation—into a single query executed within the Postgres ecosystem. By leveraging PostgresML and vector extensions such as pgvector, Korvus... -
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PyTorch-Tutorial-2nd
CV, NLP, LLM project applications, and advanced engineering deployment
PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization... -
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Docspell
Assist in organizing your piles of documents
Docspell is a personal document organizer. Or sometimes called a "Document Management System" (DMS). You'll need a scanner to convert your papers into files. Docspell can then assist in organizing the resulting mess. It can unify your files from scanners, emails, and other sources. It is targeted for home use, i.e. families, households, and also for smaller groups/companies. You can associate tags, set correspondent,s and lots of other predefined and custom metadata. If your documents are... -
Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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TensorFlow Probability
Probabilistic reasoning and statistical analysis in TensorFlow
TensorFlow Probability is a library for probabilistic reasoning and statistical analysis. TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It's for data scientists, statisticians, ML researchers, and practitioners who want to encode domain knowledge to understand data and make predictions. Since TFP inherits the benefits of TensorFlow, you can build, fit, and deploy a model... -
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GoCV
Go package for computer vision using OpenCV 4 and beyond
GoCV gives programmers who use the Go programming language access to the OpenCV 4 computer vision library. The GoCV package supports the latest releases of Go and OpenCV v4.5.4 on Linux, macOS, and Windows. Our mission is to make the Go language a “first-class” client compatible with the latest developments in the OpenCV ecosystem. Computer Vision (CV) is the ability of computers to process visual information, and perform tasks normally associated with those performed by humans. CV software... -
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OCaml
The core OCaml system: compilers, runtime system, base libraries
OCaml is a general-purpose, industrial-strength programming language with an emphasis on expressiveness and safety. OCaml’s powerful type system means more bugs are caught at compile-time, and large, complex codebases are easier to maintain. This makes it a good language for running critical code. At the same time, sophisticated inference makes the type system unobtrusive, creating a smooth developer experience. -
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Laravel Translation Manager
Manage Laravel translation files
Laravel Translation Manager is a package that adds a web-based UI and database-backed workflow for managing Laravel translation files. Instead of replacing Laravel’s built-in translation system, it imports your lang PHP/JSON files into a database so you can view, search, and edit keys and values from a browser. Once translations are updated, you can export them back to flat files so your app continues to use the standard Laravel translation loader. This workflow is especially helpful when... -
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Keras Hub
Pretrained model hub for Keras 3
Keras Hub is a repository of pre-trained models for Keras 3, offering a collection of ready-to-use models for various machine-learning tasks. KerasHub is an extension of the core Keras API; KerasHub components are provided as Layer and Model implementations. If you are familiar with Keras, congratulations. You already understand most of KerasHub. -
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Osaurus
AI edge infrastructure for macOS. Run local or cloud models
Osaurus is an open-source AI edge infrastructure platform designed specifically for macOS environments to run and manage AI models locally. The project provides a native runtime that allows applications to access large language models and AI tools directly on the user’s machine without relying entirely on cloud services. Osaurus supports running both local and remote models, enabling developers to build AI-powered applications that can operate offline or leverage external APIs when needed. The platform acts as an always-on runtime that coordinates AI tasks, tools, and workflows while enabling applications to communicate with models through standardized interfaces. ... -
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AWS Toolkit for Visual Studio Code
Local Lambda debug, CodeWhisperer, SAM/CFN syntax, etc.
...The AWS CDK Explorer enables you to work with AWS Cloud Development Kit (CDK) applications. It shows a top-level view of your CDK applications that have been synthesized in your workspace. Amazon CodeWhisperer provides inline code suggestions using machine learning and natural language processing on the contents of your current file. Supported languages include Java, Python and Javascript. -
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Triton
Development repository for the Triton language and compiler
Triton is a programming language and compiler framework specifically designed for writing highly efficient custom deep learning operations, particularly for GPUs. It aims to bridge the gap between low-level GPU programming, such as CUDA, and higher-level abstractions by providing a more productive and flexible environment for developers. Triton enables users to write optimized kernels for machine learning workloads while maintaining readability and control over performance-critical aspects like memory access patterns and parallel execution. ... -
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Violin
Open-source Video Translation Skill
Violin is an open-source video translation and dubbing tool that turns existing videos into localized versions with translated voice-over and optional subtitles. It transcribes the original speech, translates the text, generates natural-sounding speech in the target language, and remuxes the new audio back into the video. The project is designed to keep the generated speech aligned with the original timing so the final result feels closer to a real dubbed video. It can be used from the... -
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Kubeflow Trainer
Distributed AI Model Training and LLM Fine-Tuning on Kubernetes
Kubeflow Trainer is a Kubernetes-native platform designed for scalable, distributed training and fine-tuning of machine learning models, particularly large language models, across multi-node and multi-GPU environments. It extends the Kubeflow ecosystem by providing a unified framework for orchestrating training workloads using Kubernetes primitives, enabling seamless scaling from single-machine experiments to large production clusters. The platform supports a wide range of machine learning frameworks, including PyTorch, JAX, Hugging Face, DeepSpeed, and XGBoost, making it highly flexible for different AI use cases. ... -
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QMD
mini cli search engine for your docs, knowledge bases, etc.
...Users can organize content into named collections, embed documents for semantic retrieval, and then perform keyword searches, semantic searches, or hybrid natural-language queries to quickly surface the most useful information across all indexed sources. Because the entire system runs on the user’s machine, privacy is preserved and there’s no risk of exposing sensitive content to outside providers. -
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PackageCompiler
Compile your Julia Package
...You can save loaded packages and compiled functions into a file (called a sysimage) that you pass to Julia upon startup. Typically the goal is to reduce latency on your machine; for example, you could load the packages and compile the functions used in common plotting workflows using that saved image by default. In general, sysimages are not relocatable to other machines; they'll only work on the machine they were created on. -
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Jlama
Jlama is a modern LLM inference engine for Java
Jlama is a modern inference engine written entirely in Java that enables developers to run large language models locally within Java applications. Unlike frameworks that require external APIs or remote services, Jlama performs inference directly on a machine using pre-trained models. This allows organizations to integrate generative AI features into their systems while maintaining full control over data privacy and infrastructure. The engine supports a wide range of open-source model architectures and formats, including variants of Llama, Mistral, and other transformer-based models. ... -
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RLHF-Reward-Modeling
Recipes to train reward model for RLHF
RLHF-Reward-Modeling is an open-source research framework focused on training reward models used in reinforcement learning from human feedback for large language models. In RLHF pipelines, reward models are responsible for evaluating generated responses and assigning scores that guide the model toward outputs that better match human preferences. The repository provides training recipes and implementations for building reward and preference models using modern machine learning frameworks. ... -
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ModernBERT
Bringing BERT into modernity via both architecture changes and scaling
ModernBERT is an open-source research project that modernizes the classic BERT encoder architecture by incorporating recent advances in transformer design, training techniques, and efficiency improvements. The goal of the project is to bring BERT-style models up to date with the capabilities of modern large language models while preserving the strengths of bidirectional encoder architectures used for tasks such as classification, retrieval, and semantic search. ModernBERT introduces architectural improvements that enhance both training efficiency and inference performance, making the model more suitable for modern large-scale machine learning pipelines. ... -
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The LLM Evaluation guidebook
Sharing both practical insights and theoretical knowledge about LLM
The Evaluation Guidebook is an open educational resource created by Hugging Face that explains how to evaluate machine learning and large language models effectively. It compiles practical insights and theoretical knowledge gathered from real-world evaluation work, including experience managing the Open LLM Leaderboard and designing evaluation tools. The guidebook teaches developers how to design evaluation pipelines, select appropriate metrics, and interpret model performance results. ...
