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
Some more details
Browse files
README.md
CHANGED
|
@@ -21,7 +21,7 @@ It achieves the following results on the evaluation set:
|
|
| 21 |
|
| 22 |
## Model description
|
| 23 |
|
| 24 |
-
This model detects prompt
|
| 25 |
|
| 26 |
## Intended uses & limitations
|
| 27 |
|
|
@@ -29,7 +29,7 @@ More information needed
|
|
| 29 |
|
| 30 |
## Training and evaluation data
|
| 31 |
|
| 32 |
-
|
| 33 |
|
| 34 |
## Training procedure
|
| 35 |
|
|
|
|
| 21 |
|
| 22 |
## Model description
|
| 23 |
|
| 24 |
+
This model detects prompt injection attempts and classifies them as "INJECTION". Legitimate requests are classified as "LEGIT". The dataset assumes that legitimate requests are either all sorts of questions of key word searches.
|
| 25 |
|
| 26 |
## Intended uses & limitations
|
| 27 |
|
|
|
|
| 29 |
|
| 30 |
## Training and evaluation data
|
| 31 |
|
| 32 |
+
Based in the [promp-injection](https://huggingface.co/datasets/JasperLS/prompt-injections) dataset.
|
| 33 |
|
| 34 |
## Training procedure
|
| 35 |
|