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 model.safetensors from AT707/InferenceGuard-Roberta-Risk: direct link, hf CLI and curl.
- Browser
- Download file 503 MB
-
https://huggingface.co/AT707/InferenceGuard-Roberta-Risk/resolve/main/model.safetensors
- Command line
-
hf download hf://AT707/InferenceGuard-Roberta-Risk/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/AT707/InferenceGuard-Roberta-Risk/resolve/main/model.safetensors
503 MB
- Xet hash:
- a59285f871d6a624ade244f453043d3ef01a3b5920aaa5d7b936da4335e84389
- Size of remote file:
- 503 MB
- SHA256:
- 40c4073349ff3827f09503349ec1be518a66bc234991af7fb39c46f3bf8255fd
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