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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d685c6ba58f19547814c804b5950d24410c150cdba68d77b21424f55e1242b8
- Size of remote file:
- 876 MB
- SHA256:
- 0c4b54b0193c989e1697e60ef3b031aa2882831cda3118a5ba97980a16517c96
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