Instructions to use AISE-TUDelft/Custom-Activations-BERT-ReLU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AISE-TUDelft/Custom-Activations-BERT-ReLU with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AISE-TUDelft/Custom-Activations-BERT-ReLU")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AISE-TUDelft/Custom-Activations-BERT-ReLU") model = AutoModelForMaskedLM.from_pretrained("AISE-TUDelft/Custom-Activations-BERT-ReLU", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a05f389d0e34e30b991a3b1ee7f373c4cb27bf7e7d57ae1e4cea676039bfaa24
- Size of remote file:
- 39.5 MB
- SHA256:
- 2ca5d0aa4428452333d026e12121867947b1710e51552e3a8cda71724bc52c21
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