Text Classification
Scikit-learn
shell-security
shell-risk
bash
powershell
cmd
coding-agents
tf-idf
logistic-regression
cpu
research
cat-shell-risk-commander
shell-command-classification
shell-command-security
shell-risk-classification
command-risk-detection
agent-security
ai-agent-security
ai-security
tool-call-security
tool-security
posix
windows
linux
powershell-security
tfidf
shell-token-features
binary-classification
local-inference
on-device
cpu-inference
scikit-learn
json-model
a1
Eval Results (legacy)
Instructions to use patronus-studio/cat-shell-risk-commander with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use patronus-studio/cat-shell-risk-commander with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("patronus-studio/cat-shell-risk-commander", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Download validation.json from patronus-studio/cat-shell-risk-commander: direct link, hf CLI and curl.
- Browser
- Download file 273 Bytes
-
https://huggingface.co/patronus-studio/cat-shell-risk-commander/resolve/main/validation.json
- Command line
-
hf download hf://patronus-studio/cat-shell-risk-commander/validation.json
-
curl -L -o validation.json https://huggingface.co/patronus-studio/cat-shell-risk-commander/resolve/main/validation.json
273 Bytes
| { | |
| "examples": 7229, | |
| "max_absolute_score_error": 1.3128012556151702e-05, | |
| "decision_changes": { | |
| "external_commands_1pct_fpr": 0, | |
| "block_0_1pct_fpr": 0 | |
| }, | |
| "parity_ok": true, | |
| "note": "export vs in-memory, float32 accumulation; 0 decision changes required" | |
| } |