Instructions to use rasyosef/bert-tiny-amharic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rasyosef/bert-tiny-amharic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="rasyosef/bert-tiny-amharic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("rasyosef/bert-tiny-amharic") model = AutoModelForMaskedLM.from_pretrained("rasyosef/bert-tiny-amharic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Finetuning
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This model was finetuned and evaluated on the following
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- **Sentiment Classification**
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- Dataset: [amharic-sentiment](https://huggingface.co/datasets/rasyosef/amharic-sentiment)
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# Finetuning
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This model was finetuned and evaluated on the following Amharic NLP tasks
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- **Sentiment Classification**
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- Dataset: [amharic-sentiment](https://huggingface.co/datasets/rasyosef/amharic-sentiment)
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