Model reference · open weights

gpt2-small-dutch

LLMs GroNLP Text gen 1 build Licence not stated 165k dl/mo

gpt2-small-dutch is an open-weight language model from GroNLP. gpt2-small-dutch (FP32) weighs 239 MB; the smallest configuration that runs it is RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • gpt2-small-dutch is a text generation model developed by GroNLP based on the OpenAI GPT-2 architecture.
  • It features 129 million parameters and supports a context length of 1024 tokens for the Dutch language.
  • The model was created by retraining lexical embeddings and fine-tuning the full model, as described in a paper by Wietse de Vries and Malvina Nissim.

Summary of the GroNLP/gpt2-small-dutch model card, 2026-10-01

What it is

Released byGroNLP
Released2022-03-02
Parameters129M
VRAM239 MB for the weights

What it runs on

Memory and cards for gpt2-small-dutch (FP32)

239 MBweights, file size
37 MBcache per 1K tokens
508 MBruntime overhead, at least
1,024 tokenscontext max
CardRequests at onceContext maxMemory
1K each
RTX 3060 12 GB287all 1K11.6 GB
RTX 4060 Ti 16 GB388all 1K15.4 GB
RTX 3090 24 GB600all 1K23.4 GB
RTX 4090 24 GB598all 1K23.4 GB
RTX 5090 32 GB801all 1K31.0 GB
L40S 48 GB1000+all 1K44.0 GB
A100 80 GB1000+all 1K78.2 GB
H100 80 GB1000+all 1K78.1 GB
RTX PRO 6000 Blackwell 96 GB1000+all 1K93.8 GB
DGX Spark (GB10) 128 GB unified1000+all 1K107 GB
H200 141 GB1000+all 1K138 GB
B200 180 GB1000+all 1K176 GB
Memory needed at each load
Requests at once1K tokens each
1785 MB
5936 MB
81.0 GB
161.4 GB
322.0 GB
643.2 GB

One card, with vLLM's small-card settings.

From the model card

What GroNLP says about gpt2-small-dutch

Read the model card

Wietse de Vries • Malvina Nissim

Model description

This model is based on the small OpenAI GPT-2 (gpt2) model.

For details, check out our paper on arXiv and the code on Github.

Related models

Dutch

Italian

How to use

from transformers import pipeline

pipe = pipeline("text-generation", model="GroNLP/gpt2-small-dutch")
from transformers import AutoTokenizer, AutoModel, TFAutoModel

tokenizer = AutoTokenizer.from_pretrained("GroNLP/gpt2-small-dutch")
model = AutoModel.from_pretrained("GroNLP/gpt2-small-dutch")  # PyTorch
model = TFAutoModel.from_pretrained("GroNLP/gpt2-small-dutch")  # Tensorflow

BibTeX entry

@misc{devries2020good,
      title={As good as new. How to successfully recycle English GPT-2 to make models for other languages},
      author={Wietse de Vries and Malvina Nissim},
      year={2020},
      eprint={2012.05628},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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