Instructions to use Hate-speech-CNERG/indic-abusive-allInOne-MuRIL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hate-speech-CNERG/indic-abusive-allInOne-MuRIL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hate-speech-CNERG/indic-abusive-allInOne-MuRIL")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hate-speech-CNERG/indic-abusive-allInOne-MuRIL") model = AutoModelForSequenceClassification.from_pretrained("Hate-speech-CNERG/indic-abusive-allInOne-MuRIL", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2048f853fffb7e6d6e6499a7b17d4f8929e2b5fb2f2a2e0ac92e9fec21f042ff
- Size of remote file:
- 950 MB
- SHA256:
- 26bb2e923c27a5178fa6eb2aadffad439ab24b21a0ca71e34fe2ed09ec8d0fd3
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