Instructions to use HUBioDataLab/SELFormer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HUBioDataLab/SELFormer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HUBioDataLab/SELFormer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HUBioDataLab/SELFormer") model = AutoModelForMaskedLM.from_pretrained("HUBioDataLab/SELFormer") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 998ea34c356b06dd72cd5e263e9518bcc276ac1c3bca2025f34c1a572e452384
- Size of remote file:
- 2.99 kB
- SHA256:
- fd2c4928176a0ca2a2544e4ede4ad9eaebf99efcd9949bde2d51f799090224d8
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