Instructions to use uhhlt/amharic-hate-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uhhlt/amharic-hate-speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="uhhlt/amharic-hate-speech")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("uhhlt/amharic-hate-speech") model = AutoModelForSequenceClassification.from_pretrained("uhhlt/amharic-hate-speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78adc3b62b1b30f59e76822ee9c49af438fb57a6105d02554cb2569b90bc09de
- Size of remote file:
- 43.8 MB
- SHA256:
- a304ff0750c541b91d843dddca402d0e46964df4d0f402bd1d496d5441e550b9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.