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:
- a0d8c7162635388e843e6d27499492cc6303a69f800a4e33fc9db44e5c6f47d0
- Size of remote file:
- 1.59 kB
- SHA256:
- 540b29f8c5d368e254828bc79018dfdc10a2425ffe352141b6a1cdb83a5f254b
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