Model Details
Full Model IDmeta-llama/Prompt-Guard-86M
Pipeline / Tasktext-classification
Librarytransformers
Downloads (all-time)3.9M
Likes413
Last Modified11/12/2025
Author / Orgmeta-llama
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-classification", model="meta-llama/Prompt-Guard-86M")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsdeberta-v2text-classificationfacebookmetapytorchllamallama-3enlicense:llama3.1text-embeddings-inferenceendpoints_compatibledeploy:sagemakerregion:us
More Text Classification Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🏷️ Task: Text Classification
This model is designed for the Text Classification task. Explore more models for this use case.
All Text Classification Models →📊 Popularity
⬇ Downloads3.9M
❤️ Community Likes413
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.