Instructions to use NecroMOnk/safety-ds-malicious-coding-clf-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NecroMOnk/safety-ds-malicious-coding-clf-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NecroMOnk/safety-ds-malicious-coding-clf-v2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Scikit-learn
How to use NecroMOnk/safety-ds-malicious-coding-clf-v2 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("NecroMOnk/safety-ds-malicious-coding-clf-v2", "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
- Xet hash:
- 4fe334705fc7cfd52393b85e7c10b5a41526004d62e9373929ed6496b4e71b07
- Size of remote file:
- 9.06 kB
- SHA256:
- 741c1936cd82b9ca17564d8eaca9b1926fc7630be84c52490a5f95428957b75d
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