Instructions to use icelab/spacescibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use icelab/spacescibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="icelab/spacescibert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("icelab/spacescibert") model = AutoModelForMaskedLM.from_pretrained("icelab/spacescibert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22d49544c4531d486f8e1d7e51dd7d7312ce7484c314cfb18284e2cfd8172ec0
- Size of remote file:
- 1.59 kB
- SHA256:
- d948d02fe45cbdc23ff612f9eba8c2736ecfcae2cd3ed7a55153bdce1a5968c5
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