What are the hardware requirements for Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity?

Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity requires approximately 15.2 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.

Where can I download or evaluate Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity?

Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity by AlicanKiraz0 — VRAM 15.2GB, 32K context

Name: Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity
Author: AlicanKiraz0

Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity is an open-source language model by AlicanKiraz0. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: mit, Instruction-Based, Code Generating, LLM Explorer Score: 0.16.

Arxiv:1910.09700 Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-coder-... Codegen Conversational Cybersecurity En Ethicalhacking Informationsecurity Instruct Pentest Qwen2 Qwen2.5 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/AlicanKiraz0/Seneca-Cybersecurity-LLM_x_Qwen2.5-7B-CyberSecurity

Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity Parameters and Internals

LLM Name	Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity
Repository 🤗	https://huggingface.co/AlicanKiraz0/Seneca-Cybersecurity-LLM_x_Qwen2.5-7B-CyberSecurity
Base Model(s)	Qwen/Qwen2.5-Coder-7B-Instruct Qwen/Qwen2.5-Coder-7B-Instruct
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-08-24
Maintainer	AlicanKiraz0
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Supported Languages	en
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.47.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Seneca Cybersecurity LLM X Qwen2.5 7B CyberSecurity

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Rebase	986K / 15.2 GB	73	2
Qwen2.5 7B Rebase	986K / 15.2 GB	16	2
StockQwen 2.5 7B	128K / 15.2 GB	69	6
DareQwen 2.5 7B	128K / 15.2 GB	11	1
Tessa T1 7B	117K / 15.2 GB	14	10
UIGEN T1.5 7B	117K / 15.2 GB	12	6
Qwen2.5 Coder 7B Instruct	32K / 15.2 GB	2019400	765
Vibe Coder 7B Max	32K / 15.3 GB	460	1
Finsec Detector	32K / 15.2 GB	390	1
Qwen2.5 Coder Malay 7B	32K / 15.2 GB	195	1

Note: green Score (e.g. "73.2") means that the model is better than AlicanKiraz0/Seneca-Cybersecurity-LLM_x_Qwen2.5-7B-CyberSecurity.