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:
- 76d6bf98c8029394391f5bf4007341c4aed4c44a59c31be1e708a78b69e86fc4
- Size of remote file:
- 711 MB
- SHA256:
- bf6bfa6d18a57401dee5086d0266880b39988b3331518cf0d398192f9a1a90fa
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