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Holo1 3B GGUF

Developed by Mungert
Holo1-3B is a multimodal model based on the Transformer architecture, focusing on visual document retrieval tasks and performing excellently in the WebVoyager benchmark test, balancing accuracy and cost.
Downloads 583
Release Time : 6/4/2025

Model Overview

Holo1-3B is a multimodal model based on the Qwen2.5-VL architecture, suitable for visual document retrieval tasks. It achieves a good balance between accuracy and cost through technologies such as ultra-low bit quantization.

Model Features

Ultra-low bit quantization
Introduced an accuracy adaptive quantization method for ultra-low bit models (1-2 bits), which has been verified to have significant improvements through benchmark tests on Llama-3-8B.
Multi-task processing ability
Can be used for AI network monitoring, including function calls, Nmap scans, quantum readiness checks, and network monitoring tasks.
High accuracy and low cost
In the WebVoyager benchmark test, the agent based on Holo1 achieves the best balance between accuracy and cost.
UI positioning ability
Performs excellently in multiple UI positioning benchmark tests, such as Screenspot, Screenspot-V2, etc.

Model Capabilities

Visual document retrieval
Image understanding
Text generation
UI element positioning
Multimodal reasoning
Network monitoring task processing

Use Cases

Document processing
Calendar date selection
Identify and select a specific date from an image
Can accurately locate the date elements in the calendar
Network monitoring
Security audit
Perform server security audits
Can identify potential security vulnerabilities
Quantum readiness check
Check whether the server uses quantum-safe encryption
Can identify the type of encryption protocol
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