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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

MonoGame is an open-source framework that empowers developers to build cross-platform games utilizing C# and various .NET languages. It is compatible with an array of platforms, such as Windows, macOS, Linux, Android, iOS, PlayStation 4, PlayStation 5, Xbox One, and Nintendo Switch. This framework boasts an extensive range of features, including capabilities for 2D and 3D rendering, sound management, input processing, and content organization, which facilitate the creation of high-quality games in different genres. Serving as a re-imagining of Microsoft's XNA 4 API, MonoGame offers a familiar environment for those who have previously worked with XNA. Noteworthy titles crafted with MonoGame include "Streets of Rage 4," "Carrion," "Celeste," and "Stardew Valley," showcasing the framework's versatility and effectiveness. The MonoGame Foundation, along with a dedicated community, actively oversees the ongoing development and enhancement of the framework, ensuring it remains a valuable tool for game developers. With continuous updates, MonoGame strives to meet the evolving needs of the gaming industry.

Description

MonoQwen2-VL-v0.1 represents the inaugural visual document reranker aimed at improving the quality of visual documents retrieved within Retrieval-Augmented Generation (RAG) systems. Conventional RAG methodologies typically involve transforming documents into text through Optical Character Recognition (OCR), a process that can be labor-intensive and often leads to the omission of critical information, particularly for non-text elements such as graphs and tables. To combat these challenges, MonoQwen2-VL-v0.1 utilizes Visual Language Models (VLMs) that can directly interpret images, thus bypassing the need for OCR and maintaining the fidelity of visual information. The reranking process unfolds in two stages: it first employs distinct encoding to create a selection of potential documents, and subsequently applies a cross-encoding model to reorder these options based on their relevance to the given query. By implementing Low-Rank Adaptation (LoRA) atop the Qwen2-VL-2B-Instruct model, MonoQwen2-VL-v0.1 not only achieves impressive results but does so while keeping memory usage to a minimum. This innovative approach signifies a substantial advancement in the handling of visual data within RAG frameworks, paving the way for more effective information retrieval strategies.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

.NET Yes 
Android Yes 
Apple iOS Yes 
Apple iPadOS Yes 
C# Yes 
Rider Yes 
Ubuntu Yes 
Visual Studio Yes 
Visual Studio Code Yes 
Windows 11 Yes 

Integrations

.NET No 
Android No 
Apple iOS No 
Apple iPadOS No 
C# No 
Rider No 
Ubuntu No 
Visual Studio No 
Visual Studio Code No 
Windows 11 No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

MonoGame

Founded

2009

Country

United States

Website

monogame.net

Vendor Details

Company Name

LightOn

Founded

2016

Country

France

Website

www.lighton.ai/lighton-blogs/monoqwen-vision

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Product Features

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