Instructions to use icelab/spacebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use icelab/spacebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="icelab/spacebert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("icelab/spacebert") model = AutoModelForMaskedLM.from_pretrained("icelab/spacebert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a409e6240068ab5967a25d1a6651bd022a854a9bc10b20909c05e635ab1aa68a
- Size of remote file:
- 438 MB
- SHA256:
- 32f492df5496f2dc766a061b1f54febafcbb44b93ce5fdc04ae40dd138571f72
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