Search Results for "framework" - Page 37
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5470 projects for "framework" with 1 filter applied:
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Pydoll
Async Python library in automating Chromium browsers without WebDriver
...It provides a high-level API that simplifies common browser automation tasks while still offering access to low-level protocol features for advanced control. Its architecture is built around asynchronous programming using Python’s asyncio framework, enabling concurrent automation of multiple tabs and browser contexts. Pydoll also includes tools for monitoring and intercepting network traffic, allowing developers to analyze or modify requests and responses during automation workflows. It emphasizes realistic interactions and fingerprint management to reduce the likelihood of automated actions. -
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mllm
Fast Multimodal LLM on Mobile Devices
mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies such as ARM NEON and x86 AVX2 instructions. ... -
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Claude Code Skills & Plugins Hub
270+ Claude Code plugins with 739 agent skills
Claude Code Plugins Plus Skills is a large open-source ecosystem of plugins and AI “skills” designed to extend the capabilities of Claude Code development agents. The repository functions as a marketplace-style collection of hundreds of plugins and specialized skills that enable Claude Code to perform complex development, automation, and operational tasks. These plugins cover a wide range of domains including DevOps automation, security testing, API debugging, infrastructure management, and... -
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LongWriter
Unleashing 10,000+ Word Generation from Long Context LLMs
LongWriter is an open-source framework and set of large language models designed to enable ultra-long text generation that can exceed 10,000 words while maintaining coherence and structure. Traditional large language models can process large inputs but often struggle to generate long outputs due to limitations in training data and alignment strategies. LongWriter addresses this challenge by introducing a specialized dataset and training approach that encourages models to produce longer responses. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Magicoder
Empowering Code Generation with OSS-Instruct
Magicoder is an open-source family of large language models designed specifically for code generation and software development tasks. The project focuses on improving the quality and diversity of code generation by training models with a novel dataset construction approach known as OSS-Instruct. This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. By grounding training data in real... -
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Hallucination Leaderboard
Leaderboard Comparing LLM Performance at Producing Hallucinations
Hallucination Leaderboard is an open research project that tracks and compares the tendency of large language models to produce hallucinated or inaccurate information when generating summaries. The project provides a standardized benchmark that evaluates different models using a dedicated hallucination detection system known as the Hallucination Evaluation Model. Each model is tested on document summarization tasks to measure how often generated responses introduce information that is not... -
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Chat with LLMs Everywhere
Run PyTorch LLMs locally on servers, desktop and mobile
TorchChat is an open-source project from the PyTorch ecosystem designed to demonstrate how large language models can be executed efficiently across different computing environments. The project provides a compact codebase that illustrates how to run conversational AI systems using PyTorch models on laptops, servers, and mobile devices. It is intended primarily as a reference implementation that shows developers how to integrate large language models into applications without requiring a... -
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LLM Workflow Engine
Power CLI and Workflow manager for LLMs (core package)
LLM Workflow Engine is an open-source command-line framework designed to integrate large language models into automated workflows and developer environments. The platform allows users to interact with AI models directly from the terminal, enabling conversational AI access through shell commands and scripts. Instead of focusing solely on chat interactions, the system is built to embed LLM calls into larger automation pipelines where model outputs can drive decision making or trigger additional processes. ... -
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Deep Search Agent
Implement a concise and clear Deep Search Agent from 0
Deep Search Agent is an experimental demonstration project that showcases an autonomous AI agent designed to perform multi-step research and information gathering tasks. The repository illustrates how large language models can be orchestrated with tools and planning logic to execute complex search workflows rather than single-prompt responses. It typically combines reasoning, retrieval, and iterative refinement so the agent can break down questions, gather evidence, and synthesize structured... -
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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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling ecosystems. ... -
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RSC Explorer
A tool for people curious about the React Server Components protocol
...It includes a set of curated examples that demonstrate how server and client features can interoperate, helping you develop intuition for boundaries, references, and progressive rendering. This makes it useful for educators, workshop leaders, and engineers who want to demystify RSC mechanics without relying on framework-specific abstractions. In practice, it functions like a “packet analyzer” for RSC, turning a normally opaque stream into something you can study and explain. -
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Nano Events
Simple and tiny (107 bytes) event emitter library for JavaScript
Nano Events is a minimalistic, high-performance event emitter library for JavaScript. Its goal is to provide the simplest possible API to add pub/sub capabilities (emitters and listeners) to any JS object or application, while keeping overhead and bundle size extremely small. Rather than offering many complex features, nanoevents focuses on the core primitives: creating an emitter, subscribing to named events, emitting events with arbitrary data, and unsubscribing. Because of its minimal API... -
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imgui_club
Nice things to use along dear imgui
...The code emphasizes clarity and portability, so you can lift snippets directly into your own ImGui applications without heavy refactoring. Because the repo lives alongside Dear ImGui, it reflects current best practices and idioms for the framework rather than drifting into unrelated experiments. It also points to a broader ecosystem of community extensions, making it a hub for discovering higher-level widgets and specialized components. -
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react-highlight-words
React component to highlight words within a larger body of text
...The highlight output is easy to restyle via a custom tag (like mark) or inline styles, keeping the visual layer decoupled from the matching logic. Because it’s small and framework-idiomatic, it drops into tables, lists, virtualized scroll areas, and complex UIs without forcing layout changes. -
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Node.js Best Practices
The Node.js best practices list (July 2024)
This repository is a living, community-curated guide to writing robust, maintainable Node.js applications at scale. It organizes advice into clear sections—project structure, error handling, security, testing, performance, reliability, and maintainability—so teams can adopt improvements incrementally. Each guideline is phrased as a practical recommendation with motivation and trade-offs, not just a rule, which makes it easier to reach team consensus. The content aims to be... -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
...The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and attention dimensions. Because it stays close to vanilla PyTorch, you can integrate custom datasets and training loops without framework lock-in. It’s widely used as an educational reference for people learning transformers in vision and as a lightweight baseline for research prototypes. The project encourages experimentation—swap optimizers, change augmentations, or plug the transformer backbone into downstream tasks. -
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RealWorld
Exemplary fullstack Medium.com clone powered by React, Angular, Node
...The same spec is realized dozens of times (React, Vue, Svelte, Angular, Solid, Next, Remix, and many more), alongside multiple server implementations, so learners can compare idioms without guessing about feature gaps. A shared API contract and test suite keep implementations consistent and reveal framework-specific tradeoffs clearly. This makes the repo a powerful teaching tool for architecture, state management, testing, and deployment patterns at production scale. Teams also use it to evaluate new frameworks by building “yet another RealWorld” and measuring DX, bundle size, and maintainability. -
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nanochat
The best ChatGPT that $100 can buy
...The code is written to be read—concise training loops, transparent configs, and minimal wrappers—so you can audit each step, tweak it, and rerun without getting lost in framework indirection. -
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4M
4M: Massively Multimodal Masked Modeling
4M is a training framework for “any-to-any” vision foundation models that uses tokenization and masking to scale across many modalities and tasks. The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. -
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MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. ... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
DINOv2 is a self-supervised vision learning framework that produces strong, general-purpose image representations without using human labels. It builds on the DINO idea of student–teacher distillation and adapts it to modern Vision Transformer backbones with a carefully tuned recipe for data augmentation, optimization, and multi-crop training. The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval, detection, and segmentation—often requiring little or no fine-tuning. ... -
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DreamCraft3D
Official implementation of DreamCraft3D
DreamCraft3D is DeepSeek’s generative 3D modeling framework / model family that likely extends their earlier 3D efforts (e.g. Shap-E or Point-E style models) with more capability, control, or expression. The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. -
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3FS
A high-performance distributed file system
The 3FS repository (standing likely for “Feature 3F System” or similar) is focused on providing a feature extraction and transformation framework tailored to deep and large models, especially in token-based systems. Its primary aim is to support efficient and scalable feature transformation pipelines—especially for inference environments—by batching, caching, and integrating feature-based modules like segmenters, sparse retrievers, and scorers seamlessly. The repo includes APIs to define components (e.g. seg, ret, scor) that wrap or interface with external or internal modules, as well as logic to schedule and compose these feature transforms. ... -
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Pundit
Minimal authorization through OO design and pure Ruby classes
Pundit (varvet/pundit) is a Ruby gem that provides a simple and effective framework for adding authorization logic to Rails (or other Ruby) applications. It centers around policy classes—one policy per model or resource—that define what actions a given user is permitted to perform (e.g., show?, update?, destroy?). Each policy method returns a boolean, and can be structured using combinators or shared logic to keep things DRY. -
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PowerHub
A post exploitation tool based on a web application
PowerHub is a PowerShell-based automation framework designed to centralize and orchestrate common administrative tasks across Windows environments. It exposes a modular command set for inventorying systems, managing services, deploying packages, and executing remote commands with consistent logging and error handling. The project places emphasis on discoverability and reuse: scripts are organized into reusable modules and functions with clear parameter contracts so teams can compose higher-level workflows without duplicating glue code. ...