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:
- 3573eecb8270736dc3bb5daf385b6854672fb8eb977c0787bc7b212cb8633cd7
- Size of remote file:
- 347 MB
- SHA256:
- 9104e748a3f08b2e89546d581f87136c678cc2bb31e8371b8b7dc101f7d6ce57
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