Instructions to use ccaug/modernbert-base-network-attack-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ccaug/modernbert-base-network-attack-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ccaug/modernbert-base-network-attack-classifier")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ccaug/modernbert-base-network-attack-classifier") model = AutoModel.from_pretrained("ccaug/modernbert-base-network-attack-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3275185e110dd7e4091caa28ef78ece817a04c741947bec2cc90ebdc86b463d
- Size of remote file:
- 596 MB
- SHA256:
- 85cb1e3a34fa700383bad4d18738a48a77bc452bdd00428e122c215ab974fa15
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.