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
Commit History
-
Update README.md
Verified signatured50cb1d
-
Update README.md
25107c9
-
Update README.md
1f8c558
-
Update README.md
500e25a
-
Update README.md
d9cb641
-
Migrate model card from transformers-repo
Read announcement at https://huggingface.co/proxy/discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/deepset/gbert-base/README.md018d504