Text Classification
Transformers
Safetensors
English
Chinese
security
webshell-detection
malware-detection
cybersecurity
code-classification
php
asp
jsp
python
perl
Instructions to use null822/webshell-detect-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use null822/webshell-detect-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="null822/webshell-detect-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("null822/webshell-detect-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download full_codebert_model/model.safetensors from null822/webshell-detect-bert: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/null822/webshell-detect-bert/resolve/main/full_codebert_model/model.safetensors
- Command line
-
hf download hf://null822/webshell-detect-bert/full_codebert_model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/null822/webshell-detect-bert/resolve/main/full_codebert_model/model.safetensors
499 MB
- Xet hash:
- dba652cb5c642f9f2257756f6b29caa620c0dedaad1bbccf3ae2c96fe3448e21
- Size of remote file:
- 499 MB
- SHA256:
- 7fd072edd8bbdf08640cb01cbf8de24bc0ed9b6f9e4b99e5e6414947f13cc2df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.