Instructions to use SummerSigh/Safety-Policy-MiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerSigh/Safety-Policy-MiniLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SummerSigh/Safety-Policy-MiniLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SummerSigh/Safety-Policy-MiniLM") model = AutoModelForSequenceClassification.from_pretrained("SummerSigh/Safety-Policy-MiniLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SummerSigh/Safety-Policy-MiniLM: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/SummerSigh/Safety-Policy-MiniLM/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SummerSigh/Safety-Policy-MiniLM/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SummerSigh/Safety-Policy-MiniLM/resolve/main/pytorch_model.bin
471 MB
- Xet hash:
- ab4731b7ec0b4ce4ec290b407be9b2899bd897b134b41ded8f4232e5f6c4d4ad
- Size of remote file:
- 471 MB
- SHA256:
- 04c42607ceaf9dfb9bfdde750cb68ffce0091526954ed3c098d4e53e78b15728
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