Sentence Similarity
Transformers
PyTorch
mpnet
feature-extraction
cybersecurity
sentence-embedding
text-embeddings-inference
Instructions to use basel/ATTACK-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basel/ATTACK-BERT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("basel/ATTACK-BERT") model = AutoModel.from_pretrained("basel/ATTACK-BERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 190 Bytes
133854a | 1 2 3 4 5 6 7 | {
"word_embedding_dimension": 768,
"pooling_mode_cls_token": false,
"pooling_mode_mean_tokens": true,
"pooling_mode_max_tokens": false,
"pooling_mode_mean_sqrt_len_tokens": false
} |