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:
- 38c8c75b036af03969334bc52a5948893949218b660f7be5182feea8a2cb2c1e
- Size of remote file:
- 540 MB
- SHA256:
- 44ec20c0fb507650d3f8f7d68550535696945d5fed0d8dc781079a67f9da340a
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