|
|
--- |
|
|
license: apache-2.0 |
|
|
metrics: |
|
|
- accuracy |
|
|
base_model: |
|
|
- google-bert/bert-base-cased |
|
|
--- |
|
|
Uses BERT model and trained it on ~2 million most common and randomly generated passwords to check the password strength. |
|
|
|
|
|
Works well (weighted accuracy 99.4%) for passwords not exceeding 10 symbols. |
|
|
|
|
|
Note that in hosted inference API, due to the default tokenizer, there is no difference between lower and upper case letters. |
|
|
|
|
|
To use the model with the correct tokenizer, you need to invoke the model as follows: |
|
|
|
|
|
``` |
|
|
# Use a pipeline as a high-level helper - need to specify cased tokenizer |
|
|
from transformers import pipeline |
|
|
|
|
|
pipe = pipeline("text-classification", model="dima806/strong-password-checker-bert", tokenizer="bert-base-cased") |
|
|
``` |
|
|
|
|
|
See https://www.kaggle.com/code/dima806/passwords-strength-checker-bert for details. |
