What are the hardware requirements for Qwen 2.5 3B Resume Evaluator?

Qwen 2.5 3B Resume Evaluator requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen 2.5 3B Resume Evaluator and how large is it?

Qwen 2.5 3B Resume Evaluator is developed by Kami0867, a model with 3b 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 Qwen 2.5 3B Resume Evaluator?

Qwen 2.5 3B Resume Evaluator is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen 2.5 3B Resume Evaluator by Kami0867 — VRAM 0.1GB

Name: Qwen 2.5 3B Resume Evaluator
Author: Kami0867

Qwen 2.5 3B Resume Evaluator is an open-source language model by Kami0867. Features: 3b LLM, VRAM: 0.1GB, License: mit, Instruction-Based, LLM Explorer Score: 0.29.

Base model:adapter:qwen/qwen2.... Base model:qwen/qwen2.5-3b-ins... Conversational En Hr-tech Instruct Json-generation Lora Peft Qwen2.5 Recruitment Region:us Resume-screener Safetensors

Model Card on HF 🤗: https://huggingface.co/Kami0867/Qwen-2.5-3B-Resume-Evaluator

Qwen 2.5 3B Resume Evaluator Parameters and Internals

LLM Name	Qwen 2.5 3B Resume Evaluator
Repository 🤗	https://huggingface.co/Kami0867/Qwen-2.5-3B-Resume-Evaluator
Base Model(s)	Qwen/Qwen2.5-3B-Instruct Qwen/Qwen2.5-3B-Instruct
Model Size	3b
Required VRAM	0.1 GB
Updated	2026-11-01
Maintainer	Kami0867
Instruction-Based	Yes
Model Files	0.1 GB
Supported Languages	en
Model Architecture	AutoModel
License	mit
Model Max Length	131072
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	k_proj\|o_proj\|q_proj\|gate_proj\|up_proj\|down_proj\|v_proj
LoRA Alpha	24
LoRA Dropout	0.08
R Param	12
Errors	replace

Rank the Qwen 2.5 3B Resume Evaluator 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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