Instructions to use yueliu1999/GuardReasoner-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yueliu1999/GuardReasoner-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yueliu1999/GuardReasoner-3B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yueliu1999/GuardReasoner-3B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from yueliu1999/GuardReasoner-3B: direct link, hf CLI and curl.
- Browser
- Download file 439 Bytes
-
https://huggingface.co/yueliu1999/GuardReasoner-3B/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://yueliu1999/GuardReasoner-3B/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/yueliu1999/GuardReasoner-3B/resolve/main/special_tokens_map.json
439 Bytes
- Xet hash:
- 3cdbdbbe0069e9ba3cc721db6e8c179033f515b4ccaa02c47ed68f4acfef5ed6
- Size of remote file:
- 439 Bytes
- SHA256:
- 208d307467cabecb563e033fdb478b7c11a1bc6eca9a9c761bf6a303ccfce4c1
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