What are the hardware requirements for Llama 2 7B Chat Finetune?

Llama 2 7B Chat Finetune requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 2 7B Chat Finetune and how large is it?

Llama 2 7B Chat Finetune is developed by shaiksufiyan, 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 Llama 2 7B Chat Finetune?

Llama 2 7B Chat Finetune is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 2 7B Chat Finetune by shaiksufiyan — VRAM 0.1GB

Name: Llama 2 7B Chat Finetune
Author: shaiksufiyan

Llama 2 7B Chat Finetune is an open-source language model by shaiksufiyan. Features: 7b LLM, VRAM: 0.1GB, Fine-Tuned, LLM Explorer Score: 0.28.

Arxiv:1910.09700 4-bit Base model:adapter:meta-llama/... Base model:meta-llama/llama-2-... Bitsandbytes Conversational Endpoints compatible Finetuned Llama Lora Peft Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/shaiksufiyan/Llama-2-7b-chat-finetune

Llama 2 7B Chat Finetune Parameters and Internals

LLM Name	Llama 2 7B Chat Finetune
Repository 🤗	https://huggingface.co/shaiksufiyan/Llama-2-7b-chat-finetune
Base Model(s)	Llama 2 7B Chat Hf meta-llama/Llama-2-7b-chat-hf
Model Size	7b
Required VRAM	0.1 GB
Updated	2026-10-30
Maintainer	shaiksufiyan
Model Files	0.1 GB 4.2 GB
Model Architecture	AutoModelForCausalLM
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|v_proj
LoRA Alpha	16
LoRA Dropout	0.1
R Param	64

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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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