Search Results for "machine language" - Page 12
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Showing 890 open source projects for "machine language"
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Stakpak
Ship your code, on autopilot. An open source agent
Stakpak is an open-source autonomous DevOps agent designed to run continuously on a machine, managing infrastructure, deployments, and operational tasks with minimal human intervention. It acts as a persistent system-level assistant that monitors applications, executes DevOps workflows, and only alerts humans when necessary, effectively automating routine operational responsibilities. The agent is built with strong safety considerations, including guardrails that prevent destructive actions and a secure approach to handling credentials without exposing them directly to language models. ... -
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Companion notebooks for Deep Learning
Jupyter notebooks for the code samples of the book
Companion notebooks for Deep Learning is a collection of Jupyter notebooks that accompany François Chollet’s deep learning curriculum, providing hands-on implementations of key concepts using practical examples. The project covers a wide range of topics, including neural networks, computer vision, natural language processing, and sequence modeling. Each notebook is structured to combine theoretical explanations with executable code, allowing users to experiment and learn interactively. The... -
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SkillForge
Ultimate meta-skill for generating best-in-class Claude Code skills
SkillForge is a systematic methodology and tooling framework for creating high-quality AI “skills” specifically optimized for Claude Code integrations, treating skill creation as an engineering discipline rather than an ad-hoc art form. It introduces a multi-phase architecture where every input or request is triaged intelligently, analyzed deeply through structured lenses, specified formally, synthesized with automated generation, and finally subjected to multi-agent review before... -
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HY-MT
Hunyuan Translation Model Version 1.5
HY-MT (Hunyuan Translation) is a high-quality multilingual machine translation model suite developed to support mutual translation across dozens of languages with strong performance even at smaller model scales. It ships with both an 1.8 B parameter model and a larger 7 B model, the latter optimized not only for direct translation but also for formatted and contextualized output, allowing better handling of terminology and mixed-language content. -
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mcp-cli
Lighweight CLI to interact with MCP servers
mcp-cli is a lightweight, Bun-based command-line interface (CLI) tool that simplifies how developers discover, inspect, and interact with Model Context Protocol (MCP) servers from the terminal. The Model Context Protocol is an emerging open standard for connecting language models and external tools, and mcp-cli helps mitigate common pain points like context window bloat by dynamically discovering MCP servers and reducing token load during interactions. It’s designed to be fast and shell-friendly, compiling to a single standalone binary and producing machine-readable output (e.g., JSON) that plays well with other CLI tooling like jq and standard piping. mcp-cli supports both stdio and HTTP-based MCP servers, connection pooling with a lazy-spawn daemon to keep connections warm, and flexible tool filtering via easy configuration options. -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
Uncertainty Baselines is a collection of strong, well-documented training pipelines that make it straightforward to evaluate predictive uncertainty in modern machine learning models. Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems,... -
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Swift Numerics
Advanced mathematical types and functions for Swift
Swift Numerics is a foundational library that extends the Swift standard library with essential numerical protocols, types, and functions needed for scientific and systems programming. It defines generic abstractions over real and complex numbers so algorithms can be written once and work across concrete floating-point types. The package includes RealModule utilities and a full Complex type with the expected arithmetic and transcendental functions, bridging a long-standing gap for numerics... -
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Spin
Replicate your production environment locally using Docker
Stop wasting time fixing production issues you've already solved. Spin is a bash utility that improves the user experience for teams using Docker. Replicate any environment on any machine, regardless if they are running MacOS, Windows, or Linux. Centralize your infrastructure from a single configuration file using Docker. Spin is a wrapper script that dramatically improves the developer experience when working with Docker. Spin uses officially supported features and best practices from... -
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SciML Style Guide for Julia
A style guide for stylish Julia developers
The SciML Style Guide is a style guide for the Julia programming language. It is used by the SciML Open Source Scientific Machine Learning Organization. As such, it is open to discussion with the community. If the standard for code contributions is that every PR needs to support every possible input type that anyone can think of, the barrier would be too high for newcomers. Instead, the principle is to be as correct as possible to begin with, and grow the generic support over time. ... -
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JSON implementation for Ruby
JSON implementation for Ruby
This is an implementation of the JSON specification according to RFC 4627. You can think of it as a low-fat alternative to XML if you want to store data on disk or transmit it over a network rather than use a verbose markup language. Both variants of the JSON generator generate UTF-8 character sequences by default. If an:ascii_only option with a true value is given, they escape all non-ASCII and control characters with \uXXXX escape sequences, and support UTF-16 surrogate pairs in order to... -
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HASS Configurator
Configuration UI for Home Assistant
The HASS Configurator is a small web app (you access it via a web browser) that provides a filesystem browser and text-editor to modify files on the machine the configurator is running on. It has been created to allow easy configuration of Home Assistant. It is powered by Ace editor, which supports syntax highlighting for various code/markup languages. YAML files (the default language for Home Assistant configuration files) will be automatically checked for syntax errors while editing. ... -
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Label Sleuth
Open source no-code system for text annotation and building of text
...No AI knowledge needed. From task definition to working model in just a few hours! While domain experts label their data, Label Sleuth automatically trains in the background-appropriate machine learning models. To avoid wasted labeling effort, Label Sleuth employs active learning techniques to guide the user in what they should be labeled next. Domain experts can quickly start labeling their data through an intuitive user interface. Developed by researchers across industry and academia, Label Sleuth incorporates the latest research from human-computer interaction, natural language processing, and artificial intelligence. ... -
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Python Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models for NER
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models. -
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PHP Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models for NER
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models. Pass the model you want to use and the NLP Cloud token to the client during initialization. ... -
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quadplay
The quadplay fantasy console
...Supports Xbox, Playstation, SNES, Stadia, Switch, 8bitdo, touch screen, and other controllers. Hundreds of built-in sprites, sounds, and fonts. Program in PyxlScript, a friendly Python-like language. Order-independent, 4-bit alpha transparency. Native 2.5D graphics with z-order. -
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Dash Data Agent
Self-learning data agent that grounds its answers in layers of content
Dash is a self-learning data agent built by the Agno AI community that generates grounded answers to English queries over structured data by synthesizing SQL and reasoning based on six layers of context, improving automatically with each run. It sidesteps common limitations of simple text-to-SQL agents by incorporating multiple context layers — including schema structure, human annotations, known query patterns, institutional knowledge from docs, machine-discovered error patterns, and live... -
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Manfred Awesomic CV
Manfred Awesomic CV
The MAC (or Manfred Awesomic CV) is a(nother) naive attempt to create a standard open-source format to define and share CVs. The format is defined as a JSON Schema to validate CVs stored as JSON files. There are A LOT of CV formats, and some of them are a nice try to define a universal CV format, but we think that a CV should include not only what candidates are or know but also what they are interested in and what they want to become. Like most open-source projects, the first use case was... -
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Node.js Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models
...NLP Cloud serves high-performance pre-trained or custom models for NER, sentiment analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, text generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, and served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models. -
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EARTHLY
The effortless CI/CD framework that runs anywhere
Share compute and cache with Earthly Satellites. Build remotely from the comfort of your terminal. Satellites use the code in your current directory, stream logs back to you in real time, and output results (images, artifacts) back to your laptop. When used from a CI, Earthly Satellites can be used to speed up builds, as the cache is retained between runs. Earthly was engineered for readability. Most engineers are able to read an Earthfile without any prior knowledge. We took some of the... -
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A Survey of Surveys
A collection of 1000+ survey papers on Natural Language Processing
...These topics include areas such as neural machine translation, language models, computer vision, and deep learning architectures. The repository organizes hundreds of papers into thematic categories and includes references, links, and bibliographic information to facilitate research and literature exploration. -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To... -
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Catalyst.jl
Chemical reaction network and systems biology interface
...Generated models can be used with solvers throughout the broader SciML ecosystem, including higher-level SciML packages (e.g. for sensitivity analysis, parameter estimation, machine learning applications, etc). -
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GoNB
GoNB, a Go Notebook Kernel for Jupyter
Go is a compiled language, but with very fast compilation, that allows one to use it in a REPL (Read-Eval-Print-Loop) fashion, by inserting a "Compile" step in the middle of the loop -- so it's a Read-Compile-Run-Print-Loop — while still feeling very interactive. GoNB leverages that compilation speed to implement a full-featured (at least it's getting there) Jupyter notebook kernel. -
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The Grand Complete Data Science Guide
Data Science Guide With Videos And Materials
The Grand Complete Data Science Materials is a repository curated by a data-science educator that aggregates a wide range of learning resources — from basic programming and math foundation to advanced topics in machine learning, deep learning, natural language processing, computer vision, and deployment practices — into a structured, centralized collection aimed at learners seeking a comprehensive path to data science mastery. The repository bundles tutorials, lecture notes, project outlines, course materials, and references across topics like Python, statistics, ML algorithms, deep learning, NLP, data preprocessing, model evaluation, and real-world problem solving. ... -
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OpenAI DALL·E AsyncImage SwiftUI
OpenAI swift async text to image for SwiftUI app using OpenAI
...In machine learning, diffusion models, also known as diffusion probabilistic models, are a class of latent variable models. They are Markov chains trained using variational inference. The goal of diffusion models is to learn the latent structure of a dataset by modeling the way in which data points diffuse through the latent space.
