Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Mono is an open-source implementation of the Microsoft .NET Framework, backed by Microsoft and part of the .NET Foundation, adhering to ECMA standards for C# and the common language runtime. It has become a growing ecosystem supported by an enthusiastic community of contributors, positioning itself as a top choice for creating applications that operate across multiple platforms. The latest version of Mono is now available, providing comprehensive guidance on setup and internal workings. Our documentation is also open-source, inviting collaboration from anyone interested in enhancing it. We encourage community involvement; whether you want to report bugs, contribute code, or engage directly with developers, your input is valued. In essence, Mono serves as a robust platform for developers aiming to build versatile applications that function seamlessly on various systems. The collaborative spirit of the Mono project fosters innovation and continuous improvement in cross-platform development.
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
No
API Access
Has API
No
Integrations
.NET
Yes
Babel Obfuscator
Yes
C#
Yes
Docker
Yes
Nancy
Yes
Visual Studio
Yes
Yuno
Yes
Integrations
.NET
No
Babel Obfuscator
No
C#
No
Docker
No
Nancy
No
Visual Studio
No
Yuno
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
Mono
Website
www.mono-project.com
Vendor Details
Company Name
LightOn
Founded
2016
Country
France
Website
www.lighton.ai/lighton-blogs/monoqwen-vision