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:
- 601d3bdce9c4774805ce081364c115d78ec7f2b3be7ec36b525c2258438dc91e
- Size of remote file:
- 347 MB
- SHA256:
- 1e2f2b8171fbb0088a02d3ef65854eecba24250e82e6fac84d673e156d707a35
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