Instructions to use petra345/SafetyAdapter-Scorecard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use petra345/SafetyAdapter-Scorecard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="petra345/SafetyAdapter-Scorecard")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("petra345/SafetyAdapter-Scorecard") model = AutoModel.from_pretrained("petra345/SafetyAdapter-Scorecard", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Finalize SafetyAdapter-Scorecard selected checkpoint
Browse files- pytorch_model.bin +1 -3
pytorch_model.bin
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oid sha256:4e5b2fd160bba44c83bc81e653ebfa20bdd3ee4f9b208cf24776b22216bb77a0
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dummy weights for ckpt-zeta-0960
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