Text Classification
Transformers
Safetensors
English
distilbert
jailbreak-detection
prompt-safety
llm-security
classification
text-embeddings-inference
Instructions to use tech5/my-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tech5/my-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tech5/my-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tech5/my-model") model = AutoModelForSequenceClassification.from_pretrained("tech5/my-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0eee2786291646580a8a367f559c24550f578b391a5558b1f5c389973d6d541f
- Size of remote file:
- 268 MB
- SHA256:
- d174d446931751a8846053aa12434b7dcd7316f45b2ba247ef1419db82fa881b
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