What are the hardware requirements for Gpt2 Small III?

Gpt2 Small III requires approximately 0.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gpt2 Small III and how large is it?

Gpt2 Small III is developed by romanoza, a model with 124.4m 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 Gpt2 Small III?

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

Gpt2 Small III by romanoza — VRAM 0.5GB

Name: Gpt2 Small III
Author: romanoza

Gpt2 Small III is an open-source language model by romanoza. Features: 124.4m LLM, VRAM: 0.5GB, LLM Explorer Score: 0.16.

Arxiv:1910.09700 Dataset:allenai/c4 Dataset:clarin-knext/arguana-p... Dataset:jonaszpotoniec/wikiped... Dataset:juddges/pl-court-instr... Dataset:speakleash/pes-2018-20... Endpoints compatible Gpt2 Pl Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/romanoza/gpt2-small-III

Gpt2 Small III Parameters and Internals

LLM Name	Gpt2 Small III
Repository 🤗	https://huggingface.co/romanoza/gpt2-small-III
Model Size	124.4m
Required VRAM	0.5 GB
Updated	2026-07-29
Maintainer	romanoza
Model Type	gpt2
Model Files	0.5 GB
Supported Languages	pl
Model Architecture	GPT2LMHeadModel
Model Max Length	1024
Transformers Version	4.47.0
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	50257
Torch Data Type	float32
Activation Function	gelu_new
Errors	replace

Rank the Gpt2 Small III 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 romanoza/gpt2-small-III.