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Olmo 2 0325 32B Instruct GGUF

Developed by Mungert
An instruction-tuned model based on OLMo-2-0325-32B-DPO, utilizing IQ-DynamicGate ultra-low bit quantization technology, optimized for memory-constrained environments.
Downloads 15.57k
Release Time : 4/2/2025

Model Overview

This is a 32B parameter large language model, fine-tuned for instructions, supporting text generation tasks. It employs innovative IQ-DynamicGate quantization technology, maintaining high performance at 1-2 bit ultra-low precision.

Model Features

IQ-DynamicGate Ultra-low Bit Quantization
Innovative 1-2 bit quantization technology with precision adaptation strategy, reducing error propagation while maintaining extreme memory efficiency.
Hierarchical Quantization Strategy
Different quantization schemes for different model layers, retaining higher precision for key components to balance performance and efficiency.
Multi-format Support
Provides various quantization formats from BF16 to IQ3_XS, adapting to different hardware environments and performance requirements.

Model Capabilities

Text generation
Instruction following
Low-memory inference

Use Cases

Resource-constrained Environment Deployment
Edge Device Inference
Running large language models on memory-limited edge devices
IQ1_M quantized version reduces perplexity by 43.9%
CPU Inference Optimization
Efficiently running the model in CPU environments without GPU acceleration
Q4_K quantized version is suitable for memory-limited CPU inference
Research Applications
Ultra-low Bit Quantization Research
Studying the impact of 1-2 bit quantization on model performance
IQ2_S quantized version reduces perplexity by 36.9%
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