Search Results for "repository" - Page 7
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Showing 504 open source projects for "repository"
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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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SAM 3D Objects
Models for object and human mesh reconstruction
...The model is specifically designed to be robust in real-world images with clutter, occlusions, small objects, and unusual viewpoints, where many earlier 3D-from-image systems struggle. It supports both single-object and multi-object generation, allowing you to reconstruct entire scenes rather than just isolated items. The repository provides code to run inference, a quickstart demo.py script, and environment setup instructions that connect to hosted checkpoints and configuration files. Outputs are aimed at downstream usability: the reconstructed assets are textured meshes suitable for further editing, rendering, or integration into 3D pipelines and engines. -
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SAM 3D Body
Code for running inference with the SAM 3D Body Model 3DB
...The model is trained to be robust in diverse, in-the-wild conditions, so it handles varied clothing, viewpoints, and backgrounds while maintaining strong accuracy across multiple human-pose benchmarks. The repository provides Python code to run inference, utilities to download checkpoints from Hugging Face, and demo scripts that turn images into 3D meshes and visualizations. There are Jupyter notebooks that walk you through setting up the model, running it on example images, and visualizing outputs in 3D, making it approachable even if you are not a 3D expert. -
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Gemma
Gemma open-weight LLM library, from Google DeepMind
Gemma, developed by Google DeepMind, is a family of open-weights large language models (LLMs) built upon the research and technology behind Gemini. This repository provides the official implementation of the Gemma PyPI package, a JAX-based library that enables users to load, interact with, and fine-tune Gemma models. The framework supports both text and multi-modal input, allowing natural language conversations that incorporate visual content such as images. It includes APIs for conversational sampling, parameter management, and integration with fine-tuning methods like LoRA. ... -
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gpt-oss
gpt-oss-120b and gpt-oss-20b are two open-weight language models
...Both models use a native MXFP4 quantization for efficient memory use and support OpenAI’s Harmony response format, enabling transparent full chain-of-thought reasoning and advanced tool integrations such as function calling, browsing, and Python code execution. The repository provides multiple reference implementations—including PyTorch, Triton, and Metal—for educational and experimental use, as well as example clients and tools like a terminal chat app and a Responses API server. -
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Advanced Solutions Lab
This repos contains notebooks for the Advanced Solutions Lab
This repository contains Jupyter notebooks meant to be run on Vertex AI. This is maintained by Google Cloud’s Advanced Solutions Lab (ASL) team. Vertex AI is the next-generation AI Platform on the Google Cloud Platform. The material covered in this repo will take a software engineer with no exposure to machine learning to an advanced level. -
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Megatron
Ongoing research training transformer models at scale
Megatron is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA. This repository is for ongoing research on training large transformer language models at scale. We developed efficient, model-parallel (tensor, sequence, and pipeline), and multi-node pre-training of transformer based models such as GPT, BERT, and T5 using mixed precision. Megatron is also used in NeMo Megatron, a framework to help enterprises overcome the challenges of building and training sophisticated natural language processing models with billions and trillions of parameters. ... -
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OpenOutreach
Linkedin Automation Tool
...Instead of requiring a prebuilt contact list, it starts from a product description and target market definition, then uses AI to discover and prioritize likely leads on LinkedIn. The system generates search queries, evaluates candidate profiles, and learns over time which contacts best match the ideal customer profile. According to the repository, it combines large language model classification with a Bayesian machine learning layer based on profile embeddings, which helps it shift from broad exploration to more confident qualification as it gathers more decisions. It is designed to automate personalized outreach as well, including connection requests and follow-up messaging, while keeping deployment under the user’s control through a local or self-hosted setup. -
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python-whatsapp-bot
Build AI WhatsApp Bots with Pure Python
...Developers can configure the bot to receive user messages through the WhatsApp API, route them through application logic, and generate automated responses powered by AI services such as large language models. The repository includes example scripts and project structures that illustrate how to integrate OpenAI or similar AI models into the bot workflow, enabling conversational agents capable of answering questions or performing automated tasks. -
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Skill Scanner
Security Scanner for Agent Skills
This repository is a public security-focused scanning tool intended to analyze and assess AI agent skills for potential issues, quality concerns, and vulnerabilities. It acts as a scanner that inspects Agent Skills packages to flag structural problems, inconsistencies, or security flaws before they are deployed or integrated into agent workflows. -
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Materials Discovery: GNoME
AI discovers 520000 stable inorganic crystal structures for research
...Using GNoME, DeepMind identified 381,000 new stable materials, later expanding the dataset to include over 520,000 materials within 1 meV/atom of the convex hull as of August 2024. The repository provides datasets, model definitions, and interactive Colabs for exploring these materials, computing decomposition energies, and visualizing chemical families. Additionally, it includes JAX-based implementations of GNoME and Nequip—the latter being used to train interatomic potentials for dynamic simulations. -
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Granite TSFM
Foundation Models for Time Series
granite-tsfm collects public notebooks, utilities, and serving components for IBM’s Time Series Foundation Models (TSFM), giving practitioners a practical path from data prep to inference for forecasting and anomaly-detection use cases. The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted and how to wire up service components. Issues and examples in the tracker illustrate common tasks such as slicing inference windows or using pipeline helpers that return pandas DataFrames, grounding the library in day-to-day time-series operations. ... -
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DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
...In public evaluations across a variety of reasoning, code, and question-answering benchmarks (e.g. MMLU, LiveCodeBench, AIME, Codeforces, etc.), V3.2-Exp shows performance very close to or in some cases matching that of V3.1-Terminus. The repository includes tools and kernels to support the new sparse architecture—for instance, CUDA kernels, logit indexers, and open-source modules like FlashMLA and DeepGEMM are invoked for performance. -
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Z80-μLM
Z80-μLM is a 2-bit quantized language model
Z80-μLM is a retro-computing AI project that demonstrates a tiny language model (Z80-μLM) engineered to run on an 8-bit Z80 CPU by aggressively quantizing weights down to 2-bit precision. The repository provides a complete workflow where you train or fine-tune conversational models in Python, then export them into a format that can be executed on classic Z80 systems. A key deliverable is producing CP/M-compatible .COM binaries, enabling a genuinely vintage “chat with your computer” experience on real hardware or accurate emulators. ... -
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The Fable Method
How Claude Fable 5 worked, distilled into skills
...The core process classifies the request, defines completion criteria, gathers primary evidence, chooses one recommendation, makes the smallest correct change, and verifies the result. Four included skills cover planning, execution, judging completed work, and generating domain-specific adapters. The repository preserves evaluation cases, raw judge outputs, failures, and results from hundreds of agent runs. Its rules include bounded retries, authorization gates, evidence requirements, and honest caveat reporting. It can be installed as a Claude Code plugin or as standalone skills. -
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Unlimited OCR Works
Welcome the Era of One-shot Long-horizon Parsing
...The project supports single-image parsing as well as multi-page and PDF-style parsing by converting pages into images. It provides inference paths for Hugging Face Transformers, vLLM, and SGLang, which gives users several deployment options. The repository also includes example code for batch inference over image folders or PDF inputs. Overall, it is useful for researchers and developers who need advanced OCR, long-document parsing, and model-based extraction from complex visual documents. -
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The Hypersim Dataset
Photorealistic Synthetic Dataset for Holistic Indoor Scene
...Rendering pipelines and utilities allow researchers to reproduce sequences, generate novel views, or extract task-specific supervision. Because the data are perfectly labeled and controllable, Hypersim is well suited for pretraining and for studying domain transfer to real imagery. The repository acts as both a dataset index and a set of scripts for downloading, managing, and evaluating on standardized splits. -
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Bootstrap Your Own Latent (BYOL)
Usable Implementation of "Bootstrap Your Own Latent" self-supervised
Practical implementation of an astoundingly simple method for self-supervised learning that achieves a new state-of-the-art (surpassing SimCLR) without contrastive learning and having to designate negative pairs. This repository offers a module that one can easily wrap any image-based neural network (residual network, discriminator, policy network) to immediately start benefitting from unlabelled image data. There is now new evidence that batch normalization is key to making this technique work well. A new paper has successfully replaced batch norm with group norm + weight standardization, refuting that batch statistics are needed for BYOL to work. ... -
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Data Version Control
Git-based data version control for machine learning workflows
...It enables developers and data scientists to track datasets, machine learning models, and experiment results in a way that integrates with existing Git repositories. Instead of storing large datasets directly in Git, DVC keeps lightweight metadata in the repository while storing the actual data in external storage systems. This approach allows teams to manage large files efficiently while maintaining a clear history of changes to data and models. DVC also provides a pipeline system that defines the stages of machine learning workflows, making experiments reproducible and easier to manage. ... -
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Generative AI
Sample code and notebooks for Generative AI on Google Cloud
...The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and production-ready usage. The repository architecture is organised into folders like gemini/, search/, vision/, audio/, and rag-grounding/, which helps developers locate use cases by modality. It is licensed under Apache-2.0, opensourced and maintained by Google, meaning it's designed with enterprise-grade practices in mind. Overall, it serves as a practical entry point and reference library for building real-world generative AI systems on Google Cloud. -
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Tracking Any Point (TAP)
DeepMind model for tracking arbitrary points across videos & robotics
TAPNet is the official Google DeepMind repository for Tracking Any Point (TAP), bundling datasets, models, benchmarks, and demos for precise point tracking in videos. The project includes the TAP-Vid and TAPVid-3D benchmarks, which evaluate long-range tracking of arbitrary points in 2D and 3D across diverse real and synthetic videos. Its flagship models—TAPIR, BootsTAPIR, and the latest TAPNext—use matching plus temporal refinement or next-token style propagation to achieve state-of-the-art accuracy and speed on TAP-Vid. ... -
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OpenClaw Medical Skills
The largest open-source medical AI skills library for OpenClaw
...Each skill is packaged as a modular component that can be integrated into an OpenClaw-based AI assistant, allowing the agent to perform expert-level reasoning and workflows in medical contexts. Instead of relying on general-purpose language model responses, the repository equips AI agents with structured instructions and tools tailored to medical knowledge and datasets. This modular design allows developers and researchers to build AI systems that can access specialized medical reasoning processes, retrieve relevant biomedical information, and generate structured outputs suitable for analysis or downstream processing. -
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TimesFM
Pretrained time-series foundation model developed by Google Research
...Newer releases emphasize expanded context handling and more flexible forecasting outputs, including quantile forecasting so users can get uncertainty estimates rather than only point predictions. The repository also documents how model versions evolved, with newer variants focusing on efficiency and longer context windows while maintaining forecasting quality. -
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Animated Drawings
Code to accompany "A Method for Animating Children's Drawings"
...The architecture separates shape embedding (to understand user-drawn geometry) from motion embedding / generation (to produce temporally coherent movement). Users can provide rough keyframes or control constraints (pose anchors), and the system fills intermediate frames with fluid animation. The repository includes demonstration apps and notebooks where you can upload or draw shapes and watch animations play. Because the approach is data-driven, it generalizes to new drawings even with varying proportions or stylizations. -
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Chronos Forecasting
Pretrained (Language) Models for Probabilistic Time Series Forecasting
Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as... -
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Archon
The knowledge and task management backbone for AI coding assistants
Archon is an open-source “command center” designed to enhance AI coding assistant workflows by giving developers a centralized environment for knowledge management, context engineering, and task coordination across AI agents. It acts as a backend (including an MCP server) that allows different AI coding tools and assistants to share the same structured context, knowledge base, and task lists, improving consistency, productivity, and collaboration across multi-agent interactions. Users can...