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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ffa7ac161553ac2c148c8ed75a3d3bfac50b8860d2281b4431a5135726d0cfb4
- Size of remote file:
- 7.29 kB
- SHA256:
- 0ff7a50e065c6f9c04994a2cd6af2446c829484cc8c1f48bf8fc375d8546488f
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