What are the hardware requirements for Qwen2.5 Coder 7B Instruct Abliterated GGUF?

Qwen2.5 Coder 7B Instruct Abliterated GGUF requires approximately 4.2 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 Coder 7B Instruct Abliterated GGUF and how large is it?

Qwen2.5 Coder 7B Instruct Abliterated GGUF is developed by nyan-ame, a model with 7b 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 Coder 7B Instruct Abliterated GGUF?

Qwen2.5 Coder 7B Instruct Abliterated GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 Coder 7B Instruct Abliterated GGUF by nyan-ame — VRAM 4.2GB, 32K context

Name: Qwen2.5 Coder 7B Instruct Abliterated GGUF
Author: nyan-ame

Qwen2.5 Coder 7B Instruct Abliterated GGUF is an open-source language model by nyan-ame. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, Code Generating, LLM Explorer Score: 0.34.

Abliterated Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-coder-... Code Codegen Conversational Endpoints compatible Gguf Instruct Q4 Quantized Qwen Qwen2 Qwen2.5 Region:us Uncensored

Model Card on HF 🤗: https://huggingface.co/nyan-ame/Qwen2.5-Coder-7B-Instruct-Abliterated-GGUF

Qwen2.5 Coder 7B Instruct Abliterated GGUF Parameters and Internals

LLM Name	Qwen2.5 Coder 7B Instruct Abliterated GGUF
Repository 🤗	https://huggingface.co/nyan-ame/Qwen2.5-Coder-7B-Instruct-Abliterated-GGUF
Base Model(s)	Qwen/Qwen2.5-Coder-7B-Instruct Qwen/Qwen2.5-Coder-7B-Instruct
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-10-22
Maintainer	nyan-ame
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.2 GB 4.7 GB 4.5 GB 5.4 GB 5.3 GB 6.2 GB 8.1 GB 15.2 GB
GGUF Quantization	Yes
Quantization Type	gguf\|q4\|q4_k\|q5_k
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	5.20.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Errors	replace

Rank the Qwen2.5 Coder 7B Instruct Abliterated GGUF 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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