Text Classification
Transformers
Safetensors
PyTorch
English
deberta-v2
facebook
meta
llama
llama-3
text-embeddings-inference
Instructions to use meta-llama/Prompt-Guard-86M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use meta-llama/Prompt-Guard-86M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="meta-llama/Prompt-Guard-86M")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("meta-llama/Prompt-Guard-86M") model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Prompt-Guard-86M") - Inference
- Notebooks
- Google Colab
- Kaggle
Can you share the training dataset?
#19
by GoominDev - opened
Hello, the performance of Meta's Prompt Guard is impressive.
I admire this model and would like to train other BERT-based models on datasets like injection and jailbreak data.
As you may know, the most important thing when training is the dataset.
Could you share the training dataset used for the Prompt Guard model? Perhaps of the open data sources?