What are the hardware requirements for Sigpaf Ai Qwen2.5 7B?

Sigpaf Ai Qwen2.5 7B requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Sigpaf Ai Qwen2.5 7B and how large is it?

Sigpaf Ai Qwen2.5 7B is developed by tarekben, 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 Sigpaf Ai Qwen2.5 7B?

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

Sigpaf Ai Qwen2.5 7B by tarekben — VRAM 0.2GB

Name: Sigpaf Ai Qwen2.5 7B
Author: tarekben

Sigpaf Ai Qwen2.5 7B is an open-source language model by tarekben. Features: 7b LLM, VRAM: 0.2GB, Instruction-Based, LLM Explorer Score: 0.3.

Adapter Algeria Ar Base model:adapter:qwen/qwen2.... Base model:qwen/qwen2.5-7b-ins... Conversational Finetuned Fr Grh Hse Infep Instruct Lolf Lora Mfep Peft Public-accounting Qwen Qwen2.5 Region:us Safetensors Sigpaf Unsloth Vocational-training Wartilani

Model Card on HF 🤗: https://huggingface.co/tarekben/sigpaf-ai-qwen2.5-7b

Sigpaf Ai Qwen2.5 7B Parameters and Internals

LLM Name	Sigpaf Ai Qwen2.5 7B
Repository 🤗	https://huggingface.co/tarekben/sigpaf-ai-qwen2.5-7b
Base Model(s)	Qwen/Qwen2.5-7B-Instruct Qwen/Qwen2.5-7B-Instruct
Model Size	7b
Required VRAM	0.2 GB
Updated	2026-11-01
Maintainer	tarekben
Instruction-Based	Yes
Model Files	0.2 GB
Supported Languages	ar fr
Model Architecture	Adapter
Model Max Length	32768
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	up_proj\|k_proj\|o_proj\|v_proj\|q_proj\|down_proj\|gate_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16
Errors	replace

Rank the Sigpaf Ai Qwen2.5 7B 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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