Instructions to use Data-Lab/moderation_binary_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Data-Lab/moderation_binary_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Data-Lab/moderation_binary_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Data-Lab/moderation_binary_classification") model = AutoModelForSequenceClassification.from_pretrained("Data-Lab/moderation_binary_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Data-Lab/moderation_binary_classification: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/Data-Lab/moderation_binary_classification/resolve/4ed08a2d6d82e83941ae92f55a38a757636b77e7/tokenizer.json
- Command line
-
hf download hf://Data-Lab/moderation_binary_classification@4ed08a2d6d82e83941ae92f55a38a757636b77e7/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Data-Lab/moderation_binary_classification/resolve/4ed08a2d6d82e83941ae92f55a38a757636b77e7/tokenizer.json
17.1 MB
- Xet hash:
- 9b6ba5161eb5d6967b98a5bc059e28fac0793bc5fe9f5f7aedee9ebb9431e660
- Size of remote file:
- 17.1 MB
- SHA256:
- 89646f5f3e450d818fc4c0c008cf6a34e27b0c04eee20d75222aa6bfa1e8593f
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