Instructions to use ikim-uk-essen/geberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ikim-uk-essen/geberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ikim-uk-essen/geberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ikim-uk-essen/geberta-base") model = AutoModelForMaskedLM.from_pretrained("ikim-uk-essen/geberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0472f65aba101a3ed711216ec05cb69f5c1f75b878156bb4a9615e2e6e9d31db
- Size of remote file:
- 1.18 MB
- SHA256:
- f70812c0310e6f82269a45950d6036aa9e85f581b5ba9da4dae7826a6fea604d
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