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Showing 14 open source projects for "path"
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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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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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WASTE
Run the full 2.78-trillion-parameter Kimi K3 model
...Its main target is the full 2.78-trillion-parameter Kimi K3 model, including multimodal image input. The engine has no third-party runtime dependency on its CPU inference path and exposes both a CLI and C library. An optional server provides an OpenAI-compatible chat API with streaming, tools, structured output, and image support. Validation compares layers, logits, vision output, and prompt rendering against reference implementations. -
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HRM-Text
1B text generation model based on the HRM architecture
...Its training stack includes PrefixLM sequence packing, FlashAttention 3 kernels, PyTorch FSDP2, evaluation scripts, and checkpoint conversion tools. The repository supports reference pretraining runs for smaller and larger configurations, with Hopper-class GPUs expected for the attention path. It is useful for researchers and engineers exploring efficient language model pretraining, reasoning-focused architectures, and reproducible foundation model experiments. -
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Claude Code Config
My personal Claude Code configuration
...The project centralizes configuration files that instruct Claude Code how to behave in different contexts, automating repetitive tasks and enforcing coding patterns across languages or project types. Its rulesets can apply path-scoped conventions (such as for TypeScript or test files), while hooks trigger scripts on specific events like prompt submission or automated checks. Custom agents help perform specialized tasks like codebase search or documentation generation, and skills extend Claude’s capabilities with domain-specific utilities. Commands provide quick shortcuts and interactions within the Claude Code environment, helping streamline workflows. -
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Core AI Models
Model export recipes, Python primitives, and Swift runtime utilities
...The repository also contains agent skills that guide coding assistants through Core AI workflows, model authoring, and compression exploration. It is useful for developers who want a curated path from model preparation to local app integration on Apple hardware. -
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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Gorden Super PPT Skills
AI PPT Track Terminator, the strongest PPT Skill ever
Gorden Super PPT Skills is an AI presentation skill package for generating high-density visual presentations and converting them into editable PowerPoint files. The workflow is split into three skills that can be used separately or together. One skill generates image-based presentation pages from a topic or content brief. Another skill reconstructs image slides into editable PPTX files by separating backgrounds, layout structures, icons, decorations, and text. The orchestration skill chains... -
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TimesFM
Pretrained time-series foundation model developed by Google Research
TimesFM is a pretrained time-series foundation model from Google Research built for forecasting tasks, designed to generalize across many domains without requiring extensive per-dataset retraining. It provides a decoder-only model approach to forecasting, aiming for strong performance even in zero-shot or low-data settings where traditional models often struggle. The project includes code and an inference API intended to make it practical to run forecasts programmatically, with options to... -
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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. ... -
8
Map-Anything
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
...The model flexibly accepts different input combinations (images, intrinsics, poses, sparse or dense depth) and produces a rich set of outputs including per-pixel 3D points, camera intrinsics, camera poses, ray directions, confidence maps, and validity masks. Its inference path is fully feed-forward with optional mixed-precision and memory-efficient modes, making it practical to scale to long image sequences while keeping latency predictable. -
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DeepSeekMath-V2
Towards self-verifiable mathematical reasoning
...Under the hood, Math-V2 uses a massive Mixture-of-Experts (MoE) architecture (activated parameter count reportedly in the hundreds of billions) derived from DeepSeek’s experimental base architecture. For math problems, it employs a generator-verifier loop: it first generates a candidate proof (or solution path), then runs a verifier that assesses correctness and completeness. -
One Monitoring Tool for IT, OT and Cloud | Free TrialModern infrastructure spans data centers, cloud platforms and factory floors, and every blind spot between them is a risk. PRTG supports SNMP, WMI, SSH and other standard protocols to monitor IT, OT and hybrid environments through one customizable dashboard. Build the views your team needs, from network health to application performance, without switching tools. Try PRTG free for 30 days now.
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10
HiDream-I1
Open-source image generative foundation model
...It supports direct Python inference scripts, an interactive Gradio demo, and integration through the Hugging Face Diffusers library. The model uses a Llama 3.1 text encoder path and requires the proper Hugging Face access setup for automatic downloads. It is useful for researchers, developers, and creative AI builders who want an open text-to-image model with strong benchmark performance and multiple deployment options. -
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Claude Code Action
Claude Code action for GitHub PRs
Claude Code Action is a general-purpose GitHub Action that brings Anthropic’s Claude Code into pull requests and issues to answer questions, review changes, and even implement code edits. It can wake up automatically when someone mentions @claude, when a PR or issue meets certain conditions, or when a workflow step provides an explicit prompt. The action is designed to understand diffs and surrounding context, so its comments and suggestions are grounded in what actually changed rather than... -
12
Poetiq
Reproduction of Poetiq's record-breaking submission to the ARC-AGI-1
...The project demonstrates a system that orchestrates large language models (LLMs) — like those from major providers — with carefully engineered prompting, reasoning workflows, and dynamic strategies, to tackle the abstract, logic-heavy problems in ARC-AGI. Instead of relying on a single prompt or fixed strategy, their solver dynamically adapts the reasoning path, selecting what to ask or analyze next depending on intermediate results — effectively compositing reasoning, perception, and program synthesis (or symbolic manipulation) in a loop. The repository allows others to reproduce their results, experiment with different LLM backends (e.g. the user may supply keys for supported models), and observe how their adaptive meta-system handles the logic and abstraction challenges. -
13
MiniMind-O
A 0.1B Omni model trained from scratch
MiniMind-O is an educational open-source project for building a small end-to-end Omni model from scratch. It extends the MiniMind family by exploring a model that can handle text, audio, and image inputs while producing text and streaming speech outputs. The project is designed to make multimodal AI training more accessible by keeping the model size small enough for ordinary personal hardware. It includes both mini and full training data paths, allowing learners to run a complete workflow... -
14
Qwen2.5-VL-3B-Instruct
Qwen2.5-VL-3B-Instruct: Multimodal model for chat, vision & video
...It uses a SwiGLU and RMSNorm-enhanced ViT architecture and introduces mRoPE updates for robust temporal and spatial understanding. The model supports flexible image input (file path, URL, base64) and outputs structured responses like bounding boxes or JSON, making it highly versatile in commercial and research settings. It excels in a wide range of benchmarks such as DocVQA, InfoVQA, and AndroidWorld control tasks.
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