What are the hardware requirements for EverythingLM 13B V3 Peft?

EverythingLM 13B V3 Peft requires approximately 0.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed EverythingLM 13B V3 Peft and how large is it?

EverythingLM 13B V3 Peft is developed by totally-not-an-llm, a model with 13b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does EverythingLM 13B V3 Peft perform on standard benchmarks?

EverythingLM 13B V3 Peft has the following published scores: MMLU 54.7. Compare against reference models on this page or on the LLM Explorer leaderboards.

EverythingLM 13B V3 Peft by totally-not-an-llm — VRAM 0.5GB

Name: EverythingLM 13B V3 Peft
Author: totally-not-an-llm

EverythingLM 13B V3 Peft is an open-source language model by totally-not-an-llm. Features: 13b LLM, VRAM: 0.5GB, LLM Explorer Score: 0.11, Arc: 58.4, HellaSwag: 81, MMLU: 54.7, GSM8K: 5.5.

4-bit Adapter Base model:adapter:nousresearc... Base model:nousresearch/llama-... Bitsandbytes Finetuned Llama Lora Peft Region:us

Model Card on HF 🤗: https://huggingface.co/totally-not-an-llm/EverythingLM-13b-V3-peft

EverythingLM 13B V3 Peft Parameters and Internals

LLM Name	EverythingLM 13B V3 Peft
Repository 🤗	https://huggingface.co/totally-not-an-llm/EverythingLM-13b-V3-peft
Base Model(s)	Llama 2 13B Hf NousResearch/Llama-2-13b-hf
Model Size	13b
Required VRAM	0.5 GB
Updated	2026-07-17
Maintainer	totally-not-an-llm
Model Files	0.5 GB
Model Architecture	Adapter
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|k_proj\|o_proj\|gate_proj\|up_proj\|v_proj\|down_proj
LoRA Alpha	16
LoRA Dropout	0.05
R Param	32

Rank the EverythingLM 13B V3 Peft 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

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Note: green Score (e.g. "73.2") means that the model is better than totally-not-an-llm/EverythingLM-13b-V3-peft.