Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
German
Spanish
distilbert
text-embeddings-inference
Instructions to use fmops/distilbert-prompt-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fmops/distilbert-prompt-injection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fmops/distilbert-prompt-injection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fmops/distilbert-prompt-injection") model = AutoModelForSequenceClassification.from_pretrained("fmops/distilbert-prompt-injection") - Notebooks
- Google Colab
- Kaggle
File size: 137 Bytes
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license: apache-2.0
datasets:
- deepset/prompt-injections
language:
- en
- de
- es
metrics:
- accuracy
library_name: transformers
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