Instructions to use ehsanaghaei/SecureBERT_Plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ehsanaghaei/SecureBERT_Plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ehsanaghaei/SecureBERT_Plus")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ehsanaghaei/SecureBERT_Plus") model = AutoModelForMaskedLM.from_pretrained("ehsanaghaei/SecureBERT_Plus") - Inference
- Notebooks
- Google Colab
- Kaggle
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# SecureBERT+
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**SecureBERT+** is an enhanced version of [SecureBERT](https://huggingface.co/ehsanaghaei/SecureBERT), trained on a corpus **
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This model delivers an **average
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# SecureBERT+
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**SecureBERT+** is an enhanced version of [SecureBERT](https://huggingface.co/ehsanaghaei/SecureBERT), trained on a corpus **five times larger** than its predecessor and leveraging the computational power of **8×A100 GPUs**.
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This model delivers an **average 6% improvement** in Masked Language Modeling (MLM) performance compared to SecureBERT, representing a significant advancement in language understanding and representation within the cybersecurity domain.
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