Instructions to use Mehdi009/Antisemitism_Harassment_Detection_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehdi009/Antisemitism_Harassment_Detection_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mehdi009/Antisemitism_Harassment_Detection_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mehdi009/Antisemitism_Harassment_Detection_Model") model = AutoModelForSequenceClassification.from_pretrained("Mehdi009/Antisemitism_Harassment_Detection_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a1b68828c7e8a548b10adb3437de174826992284df9c8c25541c6f2975580cd
- Size of remote file:
- 5.11 kB
- SHA256:
- fe6b17bdac81cb89eabcaac3b2de0c5f27f1ccd7286ff3c7aa264ae9dc53bbe4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.