Instructions to use yueliu1999/GuardReasoner-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yueliu1999/GuardReasoner-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yueliu1999/GuardReasoner-1B")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yueliu1999/GuardReasoner-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85a403538a86711f8e22d173040d76506b993d4fc1a077c526191372034373cd
- Size of remote file:
- 21.2 kB
- SHA256:
- 598c66082b60d4b5d847858a5dbfb142d43724c0216779a19315ab133f2f9347
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