Instructions to use s2w-ai/CyBERTuned-SecurityLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s2w-ai/CyBERTuned-SecurityLLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="s2w-ai/CyBERTuned-SecurityLLM")# Load model directly from transformers import AutoTokenizer, RobertaForTokClassAndMaskedLM tokenizer = AutoTokenizer.from_pretrained("s2w-ai/CyBERTuned-SecurityLLM") model = RobertaForTokClassAndMaskedLM.from_pretrained("s2w-ai/CyBERTuned-SecurityLLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44d9a075c8734b79e8cb27efe7b5eca8ab56bb6749e5bfafd5a5202194c906ba
- Size of remote file:
- 499 MB
- SHA256:
- e14a208dd1d89932f8566a44e110b3562f993dc2fee9b8377bc57a4701b23674
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