What are the hardware requirements for Russian Babylm Urop Shivan?

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

Who developed Russian Babylm Urop Shivan and how large is it?

Russian Babylm Urop Shivan is developed by climb-mao, a model with 28.2m 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 Russian Babylm Urop Shivan?

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

Russian Babylm Urop Shivan by climb-mao — VRAM 0.1GB

Name: Russian Babylm Urop Shivan
Author: climb-mao

Russian Babylm Urop Shivan is an open-source language model by climb-mao. Features: 28.2m LLM, VRAM: 0.1GB, LLM Explorer Score: 0.2.

Endpoints compatible Generated from trainer Gpt2 Region:us Safetensors Tensorboard

Model Card on HF 🤗: https://huggingface.co/climb-mao/russian-babylm-urop-shivan

Russian Babylm Urop Shivan Parameters and Internals

LLM Name	Russian Babylm Urop Shivan
Repository 🤗	https://huggingface.co/climb-mao/russian-babylm-urop-shivan
Model Size	28.2m
Required VRAM	0.1 GB
Updated	2026-08-08
Maintainer	climb-mao
Model Type	gpt2
Model Files	0.1 GB 0.0 GB
Model Architecture	GPT2LMHeadModel
Transformers Version	4.55.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	30000
Torch Data Type	float32
Activation Function	gelu

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