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 training_args.bin from SummerSigh/Safety-Policy-MiniLM: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/SummerSigh/Safety-Policy-MiniLM/resolve/main/training_args.bin
- Command line
-
hf download hf://SummerSigh/Safety-Policy-MiniLM/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SummerSigh/Safety-Policy-MiniLM/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 5b81ab15ebf28cdb4524094caf9438dea817c0a1e39b6e1d85760525f07ea2d0
- Size of remote file:
- 3.31 kB
- SHA256:
- 98d4deafadf31d0438ab604f19beb610e72db0a0498ab53564cf1a2752fccfaf
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