What are the hardware requirements for Bormokrut?

Bormokrut requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Bormokrut and how large is it?

Bormokrut is developed by Vladniag, a model with 35.1m 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 Bormokrut?

Bormokrut is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Bormokrut by Vladniag — VRAM 0.1GB

Name: Bormokrut
Author: Vladniag

Bormokrut is an open-source language model by Vladniag. Features: 35.1m LLM, VRAM: 0.1GB, License: mit, LLM Explorer Score: 0.26.

Dataset:custom Extraction Gpt2 Region:us Routing Ru Russian Safetensors Sft Small-model Trl

Model Card on HF 🤗: https://huggingface.co/Vladniag/Bormokrut

Bormokrut Parameters and Internals

LLM Name	Bormokrut
Repository 🤗	https://huggingface.co/Vladniag/Bormokrut
Model Size	35.1m
Required VRAM	0.1 GB
Updated	2026-10-01
Maintainer	Vladniag
Model Type	gpt2
Model Files	0.1 GB 0.0 GB
Supported Languages	ru
Model Architecture	GPT2LMHeadModel
License	mit
Transformers Version	4.56.1
Tokenizer Class	T5Tokenizer
Padding Token	<pad>
Vocabulary Size	6002
Activation Function	gelu_new

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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