Instructions to use SynamicTechnologies/CYBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SynamicTechnologies/CYBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SynamicTechnologies/CYBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SynamicTechnologies/CYBERT") model = AutoModelForSequenceClassification.from_pretrained("SynamicTechnologies/CYBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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BERT model dedicated to the domain of cyber security. The model has been trained on a corpus of high-quality cyber security and computer science text and is unlikely to work outside this domain.
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# CYBERT
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BERT model dedicated to the domain of cyber security. The model has been trained on a corpus of high-quality cyber security and computer science text and is unlikely to work outside this domain.
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#Model architecture
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The model architecture used is original Roberta and tokenizer to train the corpus is Byte Level.
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#Hardware
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The model is trained on GPU NVIDIA-SMI 510.54
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