What are the hardware requirements for Japanese Gpt2 Medium?

Japanese Gpt2 Medium requires approximately 1.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Japanese Gpt2 Medium and how large is it?

Japanese Gpt2 Medium is developed by rinna, a model with 361.3m 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 Japanese Gpt2 Medium?

Japanese Gpt2 Medium is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Japanese Gpt2 Medium by rinna — VRAM 1.4GB

Name: Japanese Gpt2 Medium
Author: rinna

Japanese Gpt2 Medium is an open-source language model by rinna. Features: 361.3m LLM, VRAM: 1.4GB, License: mit, LLM Explorer Score: 0.03.

Arxiv:2404.01657 Dataset:cc100 Dataset:wikipedia Deploy:azure Endpoints compatible Gpt2 Ja Jax Lm Pytorch Region:us Safetensors Tf

Model Card on HF 🤗: https://huggingface.co/rinna/japanese-gpt2-medium

Japanese Gpt2 Medium Parameters and Internals

LLM Name	Japanese Gpt2 Medium
Repository 🤗	https://huggingface.co/rinna/japanese-gpt2-medium
Model Size	361.3m
Required VRAM	1.4 GB
Updated	2026-07-10
Maintainer	rinna
Model Type	gpt2
Model Files	1.4 GB 1.4 GB
Supported Languages	ja
Model Architecture	GPT2LMHeadModel
License	mit
Transformers Version	4.8.2
Tokenizer Class	T5Tokenizer
Padding Token	[PAD]
Vocabulary Size	32000
Activation Function	gelu_new

Rank the Japanese Gpt2 Medium 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