Instructions to use ehsanaghaei/SecureBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ehsanaghaei/SecureBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ehsanaghaei/SecureBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ehsanaghaei/SecureBERT") model = AutoModelForMaskedLM.from_pretrained("ehsanaghaei/SecureBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ehsanaghaei/SecureBERT: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/ehsanaghaei/SecureBERT/resolve/main/training_args.bin
- Command line
-
hf download hf://ehsanaghaei/SecureBERT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ehsanaghaei/SecureBERT/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- caac7f05403cb5bead2ea25776f55e44c2d4dc50c2a0f5312ce12b37bd26ac20
- Size of remote file:
- 2.86 kB
- SHA256:
- d3c9e0ecbf9a7cbe4296d2f5f31cd65dbebf3c105156255c5893727a3dd74bc2
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