Text Classification
Transformers
Safetensors
English
distilbert
agent-safety
prompt-injection
tool-use
policy-compliance
multi-label-classification
text-embeddings-inference
Instructions to use taran1812/agentguard-risk-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taran1812/agentguard-risk-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="taran1812/agentguard-risk-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("taran1812/agentguard-risk-distilbert") model = AutoModelForSequenceClassification.from_pretrained("taran1812/agentguard-risk-distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1905b2f77b1597a83690361b795cb0c3fb0b3f8746c6116bec6e6ad1ff344345
- Size of remote file:
- 5.27 kB
- SHA256:
- ea11d82e0b8b24b4999106b3c615c65439c3ec832161929cf2a960e32a0e5b12
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.