Instructions to use deepset/gbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="deepset/gbert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("deepset/gbert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download README.md from deepset/gbert-base: direct link, hf CLI and curl.
- Browser
- Download file 2.9 kB
-
https://huggingface.co/deepset/gbert-base/resolve/main/README.md
- Command line
-
hf download hf://deepset/gbert-base/README.md
-
curl -L -o README.md https://huggingface.co/deepset/gbert-base/resolve/main/README.md
language: de
license: mit
datasets:
- wikipedia
- OPUS
- OpenLegalData
German BERT base
Released, Oct 2020, this is a German BERT language model trained collaboratively by the makers of the original German BERT (aka "bert-base-german-cased") and the dbmdz BERT (aka bert-base-german-dbmdz-cased). In our paper, we outline the steps taken to train our model and show that it outperforms its predecessors.
Overview
Paper: here
Architecture: BERT base
Language: German
Performance
GermEval18 Coarse: 78.17
GermEval18 Fine: 50.90
GermEval14: 87.98
See also:
deepset/gbert-base
deepset/gbert-large
deepset/gelectra-base
deepset/gelectra-large
deepset/gelectra-base-generator
deepset/gelectra-large-generator
Authors
Branden Chan: branden.chan [at] deepset.ai
Stefan Schweter: stefan [at] schweter.eu
Timo Möller: timo.moeller [at] deepset.ai
About us
deepset is the company behind the production-ready open-source AI framework Haystack.
Some of our other work:
- Distilled roberta-base-squad2 (aka "tinyroberta-squad2")
- German BERT, GermanQuAD and GermanDPR, German embedding model
- deepset Cloud, deepset Studio
Get in touch and join the Haystack community
For more info on Haystack, visit our GitHub repo and Documentation.
We also have a Discord community open to everyone!
Twitter | LinkedIn | Discord | GitHub Discussions | Website | YouTube
By the way: we're hiring!