What are the hardware requirements for Qwen2.5 7B Hcmute Faq Lora?

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

Who developed Qwen2.5 7B Hcmute Faq Lora and how large is it?

Qwen2.5 7B Hcmute Faq Lora is developed by TicassloThang, 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 7B Hcmute Faq Lora?

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

Qwen2.5 7B Hcmute Faq Lora by TicassloThang — VRAM 0.2GB

Name: Qwen2.5 7B Hcmute Faq Lora
Author: TicassloThang

Qwen2.5 7B Hcmute Faq Lora is an open-source language model by TicassloThang. Features: 7b LLM, VRAM: 0.2GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.27.

4bit Adapter Conversational Faq Finetuned Instruct Lora Peft Qlora Quantized Qwen2.5 Region:us Safetensors Unsloth Vi Vietnamese

Model Card on HF 🤗: https://huggingface.co/TicassloThang/qwen2.5-7b-hcmute-faq-lora

Qwen2.5 7B Hcmute Faq Lora Parameters and Internals

LLM Name	Qwen2.5 7B Hcmute Faq Lora
Repository 🤗	https://huggingface.co/TicassloThang/qwen2.5-7b-hcmute-faq-lora
Base Model(s)	unsloth/qwen2.5-7b-instruct-bnb-4bit unsloth/qwen2.5-7b-instruct-bnb-4bit
Model Size	7b
Required VRAM	0.2 GB
Updated	2026-10-08
Maintainer	TicassloThang
Instruction-Based	Yes
Model Files	0.2 GB
Supported Languages	vi
Quantization Type	4bit
Model Architecture	Adapter
License	apache-2.0
Model Max Length	32768
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	down_proj\|o_proj\|up_proj\|k_proj\|v_proj\|q_proj\|gate_proj
LoRA Alpha	16
LoRA Dropout	0.05
R Param	16
Errors	replace

Rank the Qwen2.5 7B Hcmute Faq Lora 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 Qwen2.5 7B Hcmute Faq Lora

Best Alternatives	Context / RAM	Downloads	Likes
Vilaw Llm DPO V2	0K / 0.2 GB	8	1
...en2.5 Coder 7B Vietnamese LoRA	0K / 0.3 GB	45	0
Mistral Numericnlg FV	0K / 0.3 GB	6	0
Mistral Wikitable FV	0K / 0.3 GB	6	0
Mistral Charttotext FV	0K / 0.3 GB	5	0
Zephyr 7B Beta Agent Instruct	0K / 0.3 GB	11	1
Falcon 7B Instruct 4bit Lora	0K / 0 GB	0	1
Pallade Idrico 7B	0K / 0.3 GB	26	1
Lemonilia ShoriRP V0.75d	0K / 0.2 GB	8	1
Balochi Qwen 2.5 7B Instruct	0K / 0.2 GB	29	1

Note: green Score (e.g. "73.2") means that the model is better than TicassloThang/qwen2.5-7b-hcmute-faq-lora.