Instructions to use Data-Lab/moderation_layer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Data-Lab/moderation_layer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Data-Lab/moderation_layer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Data-Lab/moderation_layer") model = AutoModelForSequenceClassification.from_pretrained("Data-Lab/moderation_layer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download moderation_layer-encoder.npy from Data-Lab/moderation_layer: direct link, hf CLI and curl.
- Browser
- Download file 327 Bytes
-
https://huggingface.co/Data-Lab/moderation_layer/resolve/45ee678386cfe8f12e9909726182fef656ed6870/moderation_layer-encoder.npy
- Command line
-
hf download hf://Data-Lab/moderation_layer@45ee678386cfe8f12e9909726182fef656ed6870/moderation_layer-encoder.npy
-
curl -L -o moderation_layer-encoder.npy https://huggingface.co/Data-Lab/moderation_layer/resolve/45ee678386cfe8f12e9909726182fef656ed6870/moderation_layer-encoder.npy
327 Bytes
- Xet hash:
- 10d19af048cc838559bbd23750c113c259de5b4333026b6dfb0df2b77aa0b220
- Size of remote file:
- 327 Bytes
- SHA256:
- 3ea4ed9346dfe944eedf11ff76556ebe986a4ce15ede0803cb10d70f866329a5
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