language: de
widget:
- text: Heute ist sehr schönes Wetter in
license: mit
German GPT-2 model
In this repository we release (yet another) GPT-2 model, that was trained on ~100 GB from the "German colossal, clean Common Crawl corpus" .
The model is meant to be an entry point for fine-tuning on other texts, and it is definitely not as good or "dangerous" as the English GPT-3 model. We do not plan extensive PR or staged releases for this model 😉
Disclaimer: the presented and trained language models in this repository are for research only purposes. The GC4 corpus - that was used for training - contains crawled texts from the internet. Thus, this GPT-2 model can be considered as highly biased, resulting in a model that encodes stereotypical associations along gender, race, ethnicity and disability status. Before using and working with the released checkpoints, it is highly recommended to read:
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
from Emily M. Bender, Timnit Gebru, Angelina McMillan-Major and Shmargaret Shmitchell.
The aim of this released GPT-2 model for German is to boost research on (large) pre-trained language models for German, especially for identifying biases and how to prevent them, as most research is currently done for English only.
Changelog
06.09.2021: Initial release. Detailed information about training parameters follow soon.
Text Generation
The following code snippet can be used to generate text with this German GPT-2 model:
from transformers import pipeline
model_name = "stefan-it/german-gpt2-larger"
pipe = pipeline('text-generation', model=model_name, tokenizer=model_name)
text = pipe("Der Sinn des Lebens ist es", max_length=200)[0]["generated_text"]
print(text)
Acknowledgments
Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC). Thanks for providing access to the TFRC ❤️
Thanks to the generous support from the Hugging Face team, it is possible to download this model from their S3 storage 🤗
This project heavily profited from the amazing Hugging Face Community Week. Many thanks for the great organization and discussions during and after the week!