Text Classification
Transformers
PyTorch
Amharic
bert
Amharic
hate speech
sentiment analysis
text-embeddings-inference
Instructions to use amengemeda/amharic-hate-speech-detection-mBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amengemeda/amharic-hate-speech-detection-mBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amengemeda/amharic-hate-speech-detection-mBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amengemeda/amharic-hate-speech-detection-mBERT") model = AutoModelForSequenceClassification.from_pretrained("amengemeda/amharic-hate-speech-detection-mBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2235e6e65b4eb357018874febde4be14ad7e2f70e39e4487b84508f7ef92e6a9
- Size of remote file:
- 1.55 MB
- SHA256:
- 3a67cd5c26510fdd7e81ec75b25ef433d25f23fe8f1f198c01fe17280627e5b3
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