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GLM 4 32B 0414 GGUF

Developed by Mungert
The GLM-4-32B-0414 GGUF model is a series of powerful text generation models with various quantization formats, suitable for different hardware and memory conditions.
Downloads 817
Release Time : 4/23/2025

Model Overview

A model suitable for text generation tasks, supporting multiple quantization formats, which can be flexibly selected according to hardware conditions and requirements.

Model Features

Ultra-low bit quantization
Supports 1 - 2 bit quantization and uses an accuracy adaptive quantization method to significantly improve model efficiency.
Hierarchical strategy
Adopts layer-specific strategies to retain accuracy while maintaining memory efficiency.
Key component protection
The embedding layer/output layer uses Q5_K to reduce error propagation.
Multiple quantization formats
Provides multiple quantization formats such as BF16, F16, Q4_K, Q6_K, Q8_0 to meet different hardware requirements.

Model Capabilities

Text generation
Network monitoring
Code processing
Animation generation
Web design
SVG generation
Search-based writing

Use Cases

Network monitoring
AI network monitoring assistant
Test the performance of small open-source models in AI network monitoring, including function calls, automated Nmap scans, quantum readiness checks, and network monitoring tasks, etc.
Creative generation
Animation generation
Generate a Python program to implement a ball bouncing inside a rotating hexagon, and an HTML simulation of a small ball being released from the center of a rotating hexagon.
Web design
Design a drawing board that supports custom function plotting, and design a UI for a mobile machine learning platform.
SVG generation
Create a foggy view of a southern Chinese water town, display the LLM training process, etc.
Education
Search-based writing
Answer questions based on search results, suitable for the generation and analysis of educational content.
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