Instructions to use withsecure/DistilBERT-PromptInjectionDetectorForCVs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use withsecure/DistilBERT-PromptInjectionDetectorForCVs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="withsecure/DistilBERT-PromptInjectionDetectorForCVs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("withsecure/DistilBERT-PromptInjectionDetectorForCVs") model = AutoModelForSequenceClassification.from_pretrained("withsecure/DistilBERT-PromptInjectionDetectorForCVs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from withsecure/DistilBERT-PromptInjectionDetectorForCVs: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/withsecure/DistilBERT-PromptInjectionDetectorForCVs/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://withsecure/DistilBERT-PromptInjectionDetectorForCVs/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/withsecure/DistilBERT-PromptInjectionDetectorForCVs/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 55b5140f09cbaccd6e6ec4d9abb2b1e26b3dc92fa33d949231cf3eedf6510fea
- Size of remote file:
- 268 MB
- SHA256:
- b9f4d746c730a2c3e7fea7f434c20f3a77e5626e232b21d5d9f5c39f1c00804f
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