Search Results for "python-gtksourceview2" - Page 32
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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PS2 Cover
PS2 Covers Collection
PS2 Covers is a large-scale curated repository of PlayStation 2 game cover images designed to be used with emulators such as PCSX2 and DuckStation, providing a complete visual library for enhancing game collections. It organizes cover art by game serial identifiers, allowing automated systems to fetch the correct image for each title. The repository includes both standard and 3D-style covers, supporting different presentation preferences. It is widely used in emulator setups to create... -
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TorchCode
Practice implementing softmax, attention, GPT-2 and more
TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms,... -
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Spring AI Alibaba Examples
Spring AI Alibaba examples for building and testing AI apps
Spring AI Alibaba Examples provides a collection of example projects that demonstrate how to use Spring AI and Spring AI Alibaba across different scenarios, from basic setups to more advanced AI applications. It is designed to help developers understand core concepts, explore practical implementations, and follow best practices when building AI-powered systems using the Spring ecosystem. Each module focuses on a specific use case such as chat, image processing, audio handling, graph... -
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pix2pixHD
Synthesizing and manipulating 2048x1024 images with conditional GANs
pix2pixHD is a PyTorch-based implementation of a conditional generative adversarial network designed for high-resolution image-to-image translation, capable of producing photorealistic outputs at resolutions up to 2048×1024. It is widely used to convert structured inputs such as semantic label maps into realistic images, making it particularly valuable in applications like autonomous driving simulation, face synthesis, and scene generation. The model improves upon earlier GAN approaches by... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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DeepAudit
AI multi-agent platform for automated code security auditing system
DeepAudit is an open source code security auditing platform that uses a multi-agent architecture to analyze and identify vulnerabilities in software projects. Instead of relying solely on traditional static analysis, it simulates the reasoning process of security experts through coordinated agents responsible for orchestration, reconnaissance, analysis, and verification. DeepAudit performs deep semantic understanding of code, enabling it to detect complex vulnerabilities that span multiple... -
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YuE
Open source AI model for generating full songs from lyrics prompts
YuE is an open source project that provides a foundation model designed for full-song music generation using artificial intelligence. It focuses on transforming text inputs such as lyrics and genre prompts into complete musical compositions that include both vocal and instrumental tracks. Unlike many shorter audio generators, the model is capable of producing songs that last several minutes while maintaining coherent musical structure and alignment with the provided lyrics. YuE introduces a... -
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Machine Learning Study
This repository is for helping those interested in machine learning
Machine Learning Study is an educational repository containing tutorials and study materials related to machine learning and data science using Python. The project compiles notebooks, explanatory documents, and practical code examples that illustrate common machine learning workflows. Topics covered include supervised learning algorithms, feature engineering, model training, and performance evaluation techniques. The repository is structured as a learning resource that guides readers through building machine learning models step by step. ... -
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promptmap2
A security scanner for custom LLM applications
promptmap is an automated security scanner for custom LLM applications that focuses on prompt injection and related attack classes. The project supports both white-box and black-box testing, which means it can either run tests directly against a known model and system prompt configuration or attack an external HTTP endpoint without internal access. Its scanning workflow uses a dual-LLM architecture in which one model acts as the target being tested and another acts as a controller that... -
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ROSA
I Agent designed to interact with ROS1- and ROS2-based robotics system
ROSA, short for Robot Operating System Agent, is an AI-powered software assistant developed by NASA’s Jet Propulsion Laboratory to simplify interaction with robotic systems that use the Robot Operating System (ROS). The project provides a natural language interface that allows developers and operators to interact with robots by issuing commands or queries in conversational language. Built on top of frameworks such as LangChain and modern large language models, ROSA translates user... -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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Claude Quickstarts
A collection of projects for building deployable applications
Claude Quickstarts is a curated collection of starter projects and templates that help developers quickly begin building applications with the Claude API, making it easier to leverage Anthropic’s Claude models for real use cases. Each quickstart provides a foundational codebase with preconfigured settings and examples for common deployment scenarios, so developers can focus on customizing functionality instead of bootstrapping infrastructure. The repository includes demos, sample... -
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The Data Engineering Handbook
Links to everything you'd ever want to learn about data engineering
The Data Engineering Handbook is a comprehensive, community-curated repository that aggregates essential learning resources for anyone interested in becoming a professional data engineer. Rather than being a code project itself, it’s a learning handbook that links to books, articles, tutorials, community groups, boot camps, and real-world project examples that collectively form a roadmap to mastering data engineering skills. It includes beginner and intermediate boot camps, interview guides,... -
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AutoAgent
AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework
AutoAgent is a fully automated, zero-code LLM agent framework that lets users create agents and workflows using natural language instead of manual coding and configuration. It is structured around modes that cover both “use” and “build” scenarios: a user mode for running a ready-made multi-agent research assistant, plus editors for creating individual agents or multi-agent workflows from conversational requirements. The framework emphasizes self-managing workflow generation, where it can... -
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Acontext
Context data platform for building observable, self-learning AI agents
Acontext is a cloud-native context data platform designed to support the development and operation of advanced AI agents. It provides a unified system to store and manage contexts, multimodal messages, artifacts, and task workflows, enabling developers to engineer context effectively for their agent products. The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. Acontext also... -
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PokeeResearch-7B
Pokee Deep Research Model Open Source Repo
PokeeResearchOSS provides an open-source, agentic “deep research” model centered on a 7B backbone that can browse, read, and synthesize current information from the web. Instead of relying only on static training data, the agent performs searches, visits pages, and extracts evidence before forming answers to complex queries. It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response. The repository... -
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OpenAI Harmony
Renderer for the harmony response format to be used with gpt-oss
Harmony is a response format developed by OpenAI for use with the gpt-oss model series. It defines a structured way for language models to produce outputs, including regular text, reasoning traces, tool calls, and structured data. By mimicking the OpenAI Responses API, Harmony provides developers with a familiar interface while enabling more advanced capabilities such as multiple output channels, instruction hierarchies, and tool namespaces. The format is essential for ensuring gpt-oss... -
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OpenAI Swarm
Educational framework exploring multi-agent orchestration
Swarm focuses on making agent coordination and execution lightweight, highly controllable, and easily testable. It accomplishes this through two primitive abstractions; Agents and handoffs. An Agent encompasses instructions and tools, and can at any point choose to hand off a conversation to another Agent. These primitives are powerful enough to express rich dynamics between tools and networks of agents, allowing you to build scalable, real-world solutions while avoiding a steep learning... -
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Perfect Roadmap To Learn Data Science
Basic To Intermediate Python data science guide
Perfect Roadmap To Learn Data Science In 2025 is an extended, updated learning pathway curated for the modern data-science landscape — blending classical data-analysis, statistics, machine learning, deep learning, computer vision, NLP, as well as current deployment and MLOps practices to prepare learners for data-science careers in 2025. The roadmap is organized to guide learners systematically: starting with Python fundamentals and math/statistics, then progressing through classical machine-learning, deep-learning, data preprocessing, feature engineering, and onto domain-specific applications like computer vision or NLP, ending with deployment, real-world project construction, and best practices for production readiness. What makes it particularly valuable is its holistic nature: rather than focusing only on modeling or theory, it also addresses the broader lifecycle of data-science work, data ingestion, cleaning, EDA, feature engineering, model building, validation, deployment, etc. -
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Mini Agent
A minimal yet professional single agent demo project
Mini-Agent is a minimal yet production-minded demo project that shows how to build a serious command-line AI agent around the MiniMax-M2 model. It is designed both as a reference implementation and as a usable agent, demonstrating a full execution loop that includes planning, tool calls, and iterative refinement. The project exposes an Anthropic-compatible API interface and fully supports interleaved thinking, letting the agent alternate between reasoning steps and tool invocations during... -
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jlens
Companion code for the global workspace interpretability paper
Jacobian Lens is Anthropic’s reference implementation for examining what a language model’s internal activations are inclined to produce as text. It transports residual-stream vectors from selected layers and positions into the final-layer basis using an averaged input-output Jacobian. The transformed vectors are decoded through the model’s own unembedding into ranked vocabulary predictions. The package can fit new lenses, load saved ones, apply them to prompts, and merge results from... -
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Think Bayes 2
Text and code for the second edition of Think Bayes, by Allen Downey
Think Bayes 2 is the companion repository for the second edition of Allen B. Downey’s introduction to Bayesian statistics. It teaches Bayesian reasoning through computational methods instead of relying mainly on symbolic mathematics. Each chapter is presented as a Jupyter notebook where readers can study the text, run examples, and complete exercises. Separate solution materials help learners check their work and explore alternative approaches. The lessons cover probability distributions,... -
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LingBot-Video
Scaling Mixture-of-Experts Video Pretraining for Embodied Intelligence
LingBot-Video is a large-scale mixture-of-experts video generation model focused on embodied intelligence. It is designed to connect video synthesis with physical-world understanding instead of generating only visually appealing clips. The project includes dense and MoE model variants for text-to-image, text-to-video, and text-image-to-video workflows. Its training combines large-scale web video data with more than 70,000 hours of embodied data. A multi-reward system emphasizes aesthetics,... -
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Upscale-A-Video
Temporal-Consistent Diffusion Model for Real-World Video
Upscale-A-Video is a diffusion-based video super-resolution project from the CVPR 2024 Highlight paper “Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution.” It upscales low-resolution videos while using text prompts to guide the enhancement process. The model is designed for real-world videos where compression artifacts, blur, aging, or generated-video defects can make ordinary upscaling less reliable. The repository includes inference code, example inputs,... -
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DeepSpec
A full-stack codebase for training and evaluating speculative decoding
DeepSpec is a full-stack codebase for training and evaluating draft models used in speculative decoding. It provides the components needed to prepare data, train draft models, and measure acceptance behavior against target models. The workflow starts with data preparation, including prompt download, target answer regeneration, and target cache construction. It then trains a draft model using configuration files for different algorithms and target model setups. The evaluation pipeline... -
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Hy-MT2 is a family of fast-thinking multilingual translation models built for complex real-world translation scenarios. It includes 1.8B, 7B, and 30B-A3B model sizes, giving users options for lightweight deployment, stronger general performance, or MoE-based capacity. The models support translation across 33 languages and are designed to follow detailed translation instructions in multiple languages. They can handle tasks involving terminology, style, personalization, delimiters, structured...
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git-remote-dropbox
A transparent bridge between Git and Dropbox
git-remote-dropbox is a Git remote helper that lets Dropbox act like a real Git remote. It provides a transparent bridge between Git and a Dropbox folder or shared Dropbox folder. After installation and login, users can clone from or push to remote URLs that use the dropbox scheme. The helper preserves traditional Git remote guarantees, including atomic behavior even when multiple people operate on the repository. It can automatically create the repository directory the first time a user...