Model Card for Password-Model
Model Details
Model Description
The Password Model is intended to be used with Credential Digger in order to automatically filter false positive password discoveries.
- Developed by: SAP OSS
- Shared by [Optional]: Hugging Face
- Model type: Text Classification
- Language(s) (NLP): en
- License: Apache-2.0
- Related Models:
- Parent Model: RoBERTa
- Resources for more information:
Uses
Direct Use
The model is directly integrated into Credential Digger and can be used to filter the false positive password discoveries of a scan.
Out-of-Scope Use
The model should not be used to intentionally create hostile or alienating environments for people.
Training Details
Training Data
CodeBERT-base-mlm fine-tuned on a dataset for leak detection.
Training Procedure
Preprocessing
More information needed
Speeds, Sizes, Times
More information needed
Evaluation
More information needed
Testing Data, Factors & Metrics
Testing Data
More information needed
Factors
More information needed
Metrics
More information needed
Results
More information needed
Model Examination
More information needed
Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: More information needed
- Hours used: More information needed
- Cloud Provider: More information needed
- Compute Region: More information needed
- Carbon Emitted: More information needed
Technical Specifications [optional]
Model Architecture and Objective
More information needed
Compute Infrastructure
More information needed
Hardware
More information needed
Software
More information needed
Citation
BibTeX:
TBD
Model Card Authors [optional]
SAP OSS in collaboration with Ezi Ozoani and the Hugging Face team.
Model Card Contact
More information needed
How to Get Started with the Model
The model is directly integrated into Credential Digger and can be used to filter the false positive discoveries of a scan
Click to expand
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("SAPOSS/password-model")
model = AutoModelForSequenceClassification.from_pretrained("SAPOSS/password-model")
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