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:
- f36484677c793020969e073d73871092abd7dd41ba6e086c0fd8bfd1a4fbc7c7
- Size of remote file:
- 180 Bytes
- SHA256:
- e6bd0b30e743618c41de600b71fe491ba7060cd6f728d737371e55c6cd544352
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