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
| { | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "do_lower_case": true, | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "name_or_path": "/root/.cache/torch/sentence_transformers/sentence-transformers_all-mpnet-base-v2/", | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "special_tokens_map_file": null, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "MPNetTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |