Search Results for "reasoning models"
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Showing 8 open source projects for "reasoning models"
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1
Ollama-Laravel Package
Ollama-Laravel is a Laravel package providing seamless integration
...It also includes support for reasoning models and function calling, enabling developers to build more advanced workflows where models can trigger tools or structured actions. Real-time streaming responses are supported, allowing applications to deliver incremental outputs for better user experience. -
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ARC-AGI
The Abstraction and Reasoning Corpus
ARC-AGI is a benchmark dataset and experimental framework designed to evaluate and advance artificial general intelligence by testing systems on abstract reasoning tasks that require human-like problem-solving abilities. It consists of a curated set of tasks where models must infer patterns from input-output examples and apply those rules to new unseen cases, without relying on memorization or prior training data. The dataset is structured as grid-based puzzles, where each task requires understanding transformations such as symmetry, counting, or spatial manipulation. ... -
3
Cookbook (Google Gemini)
Examples and guides for using the Gemini API
...The repository covers a wide range of Gemini capabilities, including text, images, video, speech, robotics, and multimodal interactions. It highlights newly introduced features such as Gemini 2.5 models (Flash and Pro), Gemini’s native image generation, Veo for video generation, robotics-focused reasoning models, and Lyria for TTS and music generation. The Cookbook also includes tutorials on advanced API workflows such as grounding answers with external tools, batch-mode request handling, and live multimodal interactivity with LiveAPI. ... -
4
JavaScript Questions
A long list of (advanced) JavaScript questions, and their explanations
...It covers tricky corners—hoisting, closures, coercion, event loop, prototypes, this binding, async/await, and more—through short prompts followed by illuminating answers. Explanations often include runnable snippets and step-through reasoning so you can replicate results locally. The content is curated to sharpen mental models rather than memorize trivia, making it valuable for interviews and day-to-day debugging alike. Because questions range from beginner to advanced, you can use it as a progressive study set or a quick refresher before assessments. It’s equally helpful for mentors: the questions can anchor study groups, workshops, or code-review discussions. -
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5
Solved by Flexbox
A showcase of problems once hard or impossible to solve with CSS
Solved by Flexbox is a collection of layout patterns that demonstrates how CSS Flexbox elegantly resolves classic web design problems. It tackles everyday challenges—vertical centering, equal-height columns, sticky footers, fluid media, and responsive grids—showing concise, production-ready CSS instead of elaborate hacks. Each pattern is presented with plain HTML, clear commentary, and minimal styling, making the underlying technique easy to adapt and extend. The project emphasizes... -
6
Euler
A distributed graph deep learning framework.
...Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle. -
7
Video Nonlocal Net
Non-local Neural Networks for Video Classification
...Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo provides training recipes and models for standard datasets, as well as ablations that show how many non-local blocks to insert and at which stages. Efficient implementations keep memory and compute manageable so the blocks can be added without rewriting the entire backbone. ... -
8
DBNL
Dynamic Bayesian Network Library
DBNL is a cross-platform library that offers a variety of implementations of Bayesian networks and machine learning algorithms. It is a flexible library that covers all aspects of Bayesian netwoks from representation to reasoning and learning. It allows you to create simple static networks as well as complex temporal models with changing structure. It can handle highly non-linear dependencies between multivariate random variables. The particle based inference can answer arbitrary questions given the provided evidence and can even cope with multimodal densities. ...
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