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
Download tokenizer.json from AT707/InferenceGuard-Roberta-Risk: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/AT707/InferenceGuard-Roberta-Risk/resolve/main/tokenizer.json
- Command line
-
hf download hf://AT707/InferenceGuard-Roberta-Risk/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AT707/InferenceGuard-Roberta-Risk/resolve/main/tokenizer.json
3.56 MB
File too large to display, you can check the raw version instead.