Text Classification
Transformers
PyTorch
Safetensors
English
German
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use deepset/deberta-v3-base-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/deberta-v3-base-injection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deepset/deberta-v3-base-injection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("deepset/deberta-v3-base-injection") model = AutoModelForSequenceClassification.from_pretrained("deepset/deberta-v3-base-injection") - Inference
- Notebooks
- Google Colab
- Kaggle
Model is failing on prompts with special characters.
#6
by sourabh89 - opened
Hi , I tried a few simple examples below . It predicts them as injection.
a,b
a#b
a@b
a>b
I think the model predicts safe only if the instruction is well formatted with different special characters.
Hey @sourabh89 , thanks a lot for the info. It's true, we trained the model to be comparatively strict to only allow queries that comply with a specific use case (people searching for information in a textual database).
If your use case requires very different queries (this looks like mathematical operations?), you may want to add a representative set of legitimate queries to the data set of injections and retrain.
Hope that helps?