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LoRA Qwen2.5 7B Instruct Abliterated V3 by ngxson

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LoRA Qwen2.5 7B Instruct Abliterated V3 is an open-source language model by ngxson. Features: 7b LLM, VRAM: 0.2GB, Instruction-Based, LLM Explorer Score: 0.17.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-7b-ins...   Endpoints compatible   Instruct   Lora   Mergekit   Peft   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/ngxson/LoRA-Qwen2.5-7B-Instruct-abliterated-v3 

LoRA Qwen2.5 7B Instruct Abliterated V3 Benchmarks

LLME Score: 0.17181
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LoRA Qwen2.5 7B Instruct Abliterated V3 (ngxson/LoRA-Qwen2.5-7B-Instruct-abliterated-v3)
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LoRA Qwen2.5 7B Instruct Abliterated V3 Parameters and Internals

LLM NameLoRA Qwen2.5 7B Instruct Abliterated V3
Repository 🤗https://huggingface.co/ngxson/LoRA-Qwen2.5-7B-Instruct-abliterated-v3 
Base Model(s)  Qwen/Qwen2.5-7B-Instruct   huihui-ai/Qwen2.5-7B-Instruct-abliterated-v3   Qwen/Qwen2.5-7B-Instruct   huihui-ai/Qwen2.5-7B-Instruct-abliterated-v3
Model Size7b
Required VRAM0.2 GB
Updated2026-04-28
Maintainerngxson
Instruction-BasedYes
Model Files  0.2 GB
Model ArchitectureAutoModel
Is Biasednone
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesgate_proj|k_proj|q_proj|embed_tokens|down_proj|lm_head|up_proj|o_proj|v_proj
LoRA Alpha32
LoRA Dropout0
R Param32

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Note: green Score (e.g. "73.2") means that the model is better than ngxson/LoRA-Qwen2.5-7B-Instruct-abliterated-v3.

Rank the LoRA Qwen2.5 7B Instruct Abliterated V3 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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