Instructions to use l3cube-pune/hate-bert-hasoc-marathi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/hate-bert-hasoc-marathi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="l3cube-pune/hate-bert-hasoc-marathi")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/hate-bert-hasoc-marathi") model = AutoModelForSequenceClassification.from_pretrained("l3cube-pune/hate-bert-hasoc-marathi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (84bd971c2ac6996d0a804d72f5a1ce05c2297722) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>67f7f0e
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Initial commit for hate speech detection model trained on HASOC Marathi dataset
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