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:
- 61016fcefd4804ce07509449aec7fed4fca40da2e45445d6eab5c674499bbb1a
- Size of remote file:
- 905 Bytes
- SHA256:
- aa4cc06647fff1ac36c45cb8cfc5d400cc8f58211e66c7ee0c8bb86b0f1804db
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