Instructions to use AISE-TUDelft/Custom-Activations-BERT-GELU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AISE-TUDelft/Custom-Activations-BERT-GELU with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AISE-TUDelft/Custom-Activations-BERT-GELU")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AISE-TUDelft/Custom-Activations-BERT-GELU") model = AutoModelForMaskedLM.from_pretrained("AISE-TUDelft/Custom-Activations-BERT-GELU", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dce8a74d801a8fce143376a6ac89ab3c67fe85caee32c36413030001b90fdb5
- Size of remote file:
- 39.5 MB
- SHA256:
- 2bd9d471bd049abbdc6ae1d4201a0bf0e92dfd75363602377cfb62ed01647b6c
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