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")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("deepset/gbert-base", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94db12936e7000f35a16bd5a8b023d85d7aff4c1cfed4d5dd70c17b46eaea69c
- Size of remote file:
- 442 MB
- SHA256:
- 1c3d31aa6461261d8714a4ba57033437dba5afce502be1faaa068368132461fe
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