Text Classification
Transformers
PyTorch
Safetensors
inferenceguard-roberta
privacy
inferential-privacy
roberta
multi-task-classification
risk-estimation
integrated-gradients
llm-firewall
Instructions to use AT707/InferenceGuard-Roberta-Risk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AT707/InferenceGuard-Roberta-Risk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AT707/InferenceGuard-Roberta-Risk")# pip install -U transformers accelerate # Load model directly from transformers import RobertaRiskClassifier model = RobertaRiskClassifier.from_pretrained("AT707/InferenceGuard-Roberta-Risk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 442 Bytes
048bac6 b445e0b 048bac6 b445e0b 048bac6 b445e0b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"architectures": [
"RobertaRiskClassifier"
],
"attributes": [
"age",
"location",
"occupation",
"education"
],
"base_model_name": "roberta-base",
"classifier_dropout": 0.1,
"dtype": "float32",
"hidden_size": 768,
"model_type": "inferenceguard-roberta",
"num_classes_per_head": 1,
"num_heads": 4,
"temperature_values": [
1.0,
1.0,
1.0,
1.0
],
"transformers_version": "5.20.2"
}
|