Instructions to use zjunlp/SafeEdit-Safety-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zjunlp/SafeEdit-Safety-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zjunlp/SafeEdit-Safety-Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zjunlp/SafeEdit-Safety-Classifier") model = AutoModelForSequenceClassification.from_pretrained("zjunlp/SafeEdit-Safety-Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zjunlp/SafeEdit-Safety-Classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/zjunlp/SafeEdit-Safety-Classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zjunlp/SafeEdit-Safety-Classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zjunlp/SafeEdit-Safety-Classifier/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- e2c62b1caf2da5d0cc507cebdd77d1e7f8ae4ea2b6ff6385edc25178b67f0abe
- Size of remote file:
- 1.42 GB
- SHA256:
- c513ca0bf6c12cd5bc9b5d07234b354bda33509ea40c75a0c56ab98532e05bb4
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