What are the hardware requirements for Qwen2.5 1.5B Instruct RefusalAblated?

Qwen2.5 1.5B Instruct RefusalAblated requires approximately 3.1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 1.5B Instruct RefusalAblated and how large is it?

Qwen2.5 1.5B Instruct RefusalAblated is developed by xdchinza, a model with 1.5b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Qwen2.5 1.5B Instruct RefusalAblated?

Qwen2.5 1.5B Instruct RefusalAblated is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 1.5B Instruct RefusalAblated by xdchinza — VRAM 3.1GB, 32K context

Name: Qwen2.5 1.5B Instruct RefusalAblated
Author: xdchinza

Qwen2.5 1.5B Instruct RefusalAblated is an open-source language model by xdchinza. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.3.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-1.5b-i... Conversational Endpoints compatible Instruct Interpretability Mechanistic-interpretability Qwen2 Refusal-ablation Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/xdchinza/Qwen2.5-1.5B-Instruct-RefusalAblated

Qwen2.5 1.5B Instruct RefusalAblated Parameters and Internals

LLM Name	Qwen2.5 1.5B Instruct RefusalAblated
Repository 🤗	https://huggingface.co/xdchinza/Qwen2.5-1.5B-Instruct-RefusalAblated
Base Model(s)	Qwen/Qwen2.5-1.5B-Instruct Qwen/Qwen2.5-1.5B-Instruct
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-10-11
Maintainer	xdchinza
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	5.17.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the Qwen2.5 1.5B Instruct RefusalAblated 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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